JP2008262549A - Authentication method and authentication apparatus - Google Patents

Abstract

An object of the present invention is to provide an authentication method and an authentication apparatus that can improve security by making it more difficult to perform annoying acts by a “bot” having a function of recognizing characters in an image.
An authentication method in an authentication apparatus for authenticating a user, wherein an authentication image in which an image corresponding to a character and / or symbol is provided on a background, the background and the character and / or symbol being An authentication image generating step for generating an authentication image having no edge due to an image density difference between the corresponding images, and an authentication image for presenting the authentication image generated in the authentication image generating step to the user Authentication is performed by comparing the information of characters and / or symbols input by the user based on the authentication image presented in the presenting step and the authentication image presenting step with the characters and / or symbols in the authentication image. And an authentication step to be performed.
[Selection] Figure 3

Description

  The present invention relates to an authentication method and an authentication apparatus.

  Currently, electronic bulletin boards on the Internet, web logs, and user participation type content generation systems such as Wiki have come to be widely used. In many of such systems, a user can not only browse information but also freely post information by performing simple user registration.

  However, by using a computer program called a “bot” that exploits these features and automatically communicates with the server, it obtains indiscriminately a large number of accounts for such sites, and the contents of each site. Annoying acts such as posting advertisements that are completely unrelated to this are also increasing. In addition, a free e-mail address acquisition service automatically obtains a large number of e-mail addresses illegally using such “bots” and uses the acquired e-mail addresses to indiscriminately identify unspecified people. It is often used for various nuisances on the Internet, such as sending spam mails or using it for the purpose of nuisances to the above-mentioned user participation type content generation system.

  In order to prevent such annoying behavior, a system has been devised that determines whether the user is an actual person or the above-mentioned “bot” and allows posting only when the person is identified as a person. . Such a system is generally called an anti-robot test, and it is a system that allows humans to post, but presents information that is identifiable to humans but cannot or cannot be identified by current computer programs as a test. It has become. Specifically, the above-mentioned program called “bot” analyzes messages between the client and the server that are mainly exchanged with text information, and automatically generates a spoofed message from the client side. In order to transmit a message from the client side, the system requires a result obtained by interpreting information that can be interpreted only by an actual person other than the character information presented from the server side.

  A visual anti-robot that presents an image containing a plurality of rasterized characters and symbols as information other than such character information and inputs the result of reading the characters and symbol strings in the image into a separately prepared input form Tests are often used. This is because it is easy for humans to read characters in an image, but it is difficult to do this with a computer program, or the benefits obtained from the above-mentioned nuisance and It is a system that utilizes the fact that the cost to execute is not commensurate.

However, it is also true that such protection has been weakened year by year as character recognition technology in images such as OCR (Optical Character Recognition) progresses. In an attempt to obstruct character recognition by OCR, in a technique called Captcha (registered trademark), image data using characters or symbols that are distorted or obscured is used.
JP 2005-322214 A

  However, in the system using the visual anti-robot test described in Patent Document 1 and the background art, it is technically easy to deceive and break through the system in view of the recent improvement in image recognition technology by computers. Therefore, there is a problem that the cost is reduced and the strength of the system is weakened.

  The present invention has been invented in order to solve this problem in view of the above points, and by making it more difficult to carry out nuisance by a “bot” having a function of recognizing characters in an image. It is an object of the present invention to provide an authentication method and an authentication device that can improve security.

  In order to achieve the above object, an authentication method of the present invention is an authentication method in an authentication apparatus for authenticating a user, and is an authentication image in which an image corresponding to characters and / or symbols is provided on a background. An authentication image generation step for generating an authentication image in which no edge due to an image density difference exists between the background and the image corresponding to the character and / or symbol, and the authentication image generation step. Authentication image presenting step for presenting the authentication image to the user, information on characters and / or symbols inputted by the user based on the authentication image presented in the authentication image presenting step, and characters in the authentication image And / or an authentication step of performing authentication by comparing the symbols.

  In order to achieve the above object, the authentication image generated in the authentication image generation step of the present invention is different from the first texture on the background consisting of the first texture, and the The image may be configured to be provided with authentication information including a second texture that forms an image corresponding to a character and / or a symbol.

  Moreover, in order to achieve said objective, it can comprise so that the average value of the image density of said 1st texture and said 2nd texture of this invention may be substantially equal.

  In order to achieve the above object, the authentication image generated in the authentication image generation step of the present invention is a stereogram image in which an image corresponding to the character and / or symbol is embedded. Can be configured.

  In order to achieve the above object, the authentication image generated in the authentication image generation step of the present invention is an image in which each of the characters and / or symbols is composed of a plurality of characters and / or symbols. It can be configured to be.

  In order to achieve the above object, the authentication image generated in the authentication image generation step of the present invention is an image composed of point groups indicating the characteristics of the characters and / or symbols. Can be configured.

  In order to achieve the above object, in the authentication image presenting step of the present invention, the user is further prompted to select characters and / or symbols included in the authentication image. In the authentication step, the authentication The authentication is performed by comparing the character and / or symbol information selected by the user based on the authentication image presented in the authentication image presenting step with the character and / or symbol in the authentication image. Can do.

  In order to achieve the above object, the authentication image presenting step of the present invention further includes any one or more satisfying a predetermined condition among the plurality of authentication images and the plurality of authentication images. The authentication is performed by comparing the predetermined image with the authentication image selected by the user based on the authentication image presented in the authentication image presenting step. Can be configured.

  In order to achieve the above object, an authentication method of the present invention is an authentication method in an authentication apparatus for authenticating a user, and an image corresponding to a character and / or a symbol on a background consisting of a first texture. An authentication moving image generating step for generating an authentication moving image in which authentication information including a second texture that forms the image and a positional relationship between the background and the authentication information changes with time, and the authentication An authentication video presentation step for presenting to the user the authentication video generated in the video generation step, and character and / or symbol information input by the user based on the authentication video presented in the authentication video presentation step; An authentication step of performing authentication by comparing characters and / or symbols in the authentication moving image.

  In order to achieve the above object, the authentication moving image generated in the authentication moving image generation step of the present invention is a continuation of an image composed of point groups indicating the characteristics of the characters and / or symbols. It can be constituted as follows.

  In order to achieve the above object, the authentication video presentation step of the present invention further prompts the user to select characters and / or symbols included in the authentication video, and the authentication step The authentication is performed by comparing the character and / or symbol information selected by the user based on the authentication video presented in the authentication video presentation step with the characters and / or symbols in the authentication video. Can do.

  In order to achieve the above object, in the authentication moving image presentation step of the present invention, the authentication moving image presenting step further satisfies any one or more conditions satisfying a predetermined condition among the plurality of authentication moving images and the plurality of authentication moving images. The user is prompted to select the authentication, and the authentication step performs authentication by comparing the authentication video selected by the user based on the authentication video presented in the authentication video presentation step with the predetermined condition. Can be configured.

  In order to achieve the above object, an authentication apparatus of the present invention is an authentication apparatus for authenticating a user, and is an authentication image in which an image corresponding to characters and / or symbols is provided on a background. An authentication image generating means for generating an authentication image in which an edge due to an image density difference does not exist between the background and the image corresponding to the character and / or symbol, and the authentication image generating means Authentication image presentation means for presenting an authentication image to the user, information on characters and / or symbols input by the user based on the authentication image presented by the authentication image presentation means, characters in the authentication image, and And / or an authentication unit that performs authentication by comparing the symbols.

  In order to achieve the above object, an authentication apparatus according to the present invention is an authentication apparatus for authenticating a user, which is different from the first texture on a background made of the first texture, and includes characters and / or Alternatively, an authentication image generation unit that generates an authentication image provided with authentication information including a second texture that forms an image corresponding to a symbol, and an authentication image generated by the authentication image generation unit Authentication image presenting means presented to the user, information on characters and / or symbols input by the user based on the authentication image presented by the authentication image presenting means, and characters and / or symbols in the authentication image Authentication means for performing authentication by comparison.

  In order to achieve the above object, an authentication apparatus of the present invention is an authentication apparatus for authenticating a user, and generates a stereogram image in which an image corresponding to a character and / or a symbol is embedded as an authentication image. An authentication image generating means, an authentication image presenting step for presenting the authentication image generated by the authentication image generating means to the user, and a user based on the authentication image presented by the authentication image presenting means. It can comprise so that it may have an authentication means which authenticates by comparing the information of the input character and / or symbol, and the character and / or symbol in the said image for authentication.

  In order to achieve the above object, an authentication apparatus according to the present invention is an authentication apparatus for authenticating a user, and forms an image corresponding to characters and / or symbols on a background made of a first texture. An authentication moving image generating means for generating an authentication moving image in which authentication information comprising a second texture is provided, and a positional relationship between the background and the authentication information changes with time, and the authentication moving image generation means Authentication moving image presenting means for presenting the authentication moving image generated by the user, information on characters and / or symbols input by the user based on the authentication moving image presented by the authentication moving image presenting means, and the authentication An authentication unit that performs authentication by comparing characters and / or symbols in a moving image can be provided.

  In order to achieve the above object, an authentication apparatus of the present invention is an authentication apparatus for authenticating a user, and is an image corresponding to a character and / or a symbol, wherein each of the character and / or the symbol is Authentication image generating means for generating an image composed of a plurality of characters and / or symbols as an authentication image; and authentication image presenting means for presenting the authentication image generated by the authentication image generating means to the user. Authentication means for performing authentication by comparing character and / or symbol information input by the user based on the authentication image presented by the authentication image presenting means with the characters and / or symbols in the authentication image It can comprise so that.

  ADVANTAGE OF THE INVENTION According to this invention, the authentication method and authentication apparatus which implement | achieve the improvement of security can be provided by making it more difficult to perform the troublesome act by "bot" which has the function to recognize the character in an image.

  The best mode for carrying out the present invention will be described below with reference to the drawings. A visual anti-robot test system will be described as an example of the authentication system according to the present invention, but the present invention is not limited to this case. Further, a server apparatus which is an example of a general computer apparatus will be described as an example of an authentication apparatus, but it is not limited to this case.

[First Embodiment]
Hereinafter, the first embodiment of the present invention will be described with reference to FIGS.

(Authentication system)
FIG. 1 is a diagram illustrating an example of an authentication system according to the first embodiment. In FIG. 1, an authentication system 1 is a client / server system having client devices 10A, 10B, 10C (hereinafter collectively referred to as client device 10) and a server device 20.

  The client device 10 and the server device 20 are general computer devices including a CPU (Central Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), and the like (not shown).

  With the system configuration described above, the authentication system 1 determines whether the user of the client device 10 is an actual person or an automated computer program. Communication between the client device 10 and the server device 20 is performed via HTTP (HyperText Transfer Protocol) or HTTPS (HyperText Transfer Protocol Security) which is encrypted HTTP. In response to a request from the client device 10, the server device 20 transmits information in the HTML (HyperText Markup Language) format to the client device 10.

  Note that the communication protocol used for communication between the client device 10 and the server device 20 is not limited to the above HTTP and HTTPS.

(Function structure)
FIG. 2 is a diagram illustrating an example of a functional configuration of the authentication system according to the first embodiment. In FIG. 2, the client device 10 includes an input unit 110, a display unit 120, a communication unit 130, a control unit 140, and the like. The server device 20 includes an authentication unit 210, an authentication image generation unit (authentication video generation unit) 220, an authentication image presentation unit (authentication video presentation unit) 230, a communication unit 240, a service provision unit 250, and a control unit. 260 or the like.

  First, each functional unit included in the client device 10 will be described.

  The input unit 110 inputs various instructions from the user of the client device 10. For example, a service request instruction for receiving a service provision such as a Web service from the server device 20.

  The display unit 120 displays on a display device such as a liquid crystal display device (not shown) of the client device 10. The communication unit 130 is an interface unit for performing communication with the server device 20. The control unit 140 performs various controls of the client device 10 including the input unit 110, the display unit 120, and the communication unit 130 described above.

  Subsequently, each functional unit included in the server device 20 will be described.

  The authentication unit 210 performs authentication based on information received from the client device 10. For example, it is determined (authenticated) whether the user of the client device 10 is an actual person or an automated computer program. Furthermore, user authentication of the client device 10 is performed based on the user name, password, etc. received from the client device 10. These operations will be described later with reference to FIG.

  The authentication image generation unit 220 generates an authentication image (or authentication moving image) according to the present invention. Examples of the generated authentication image (or authentication moving image) will be described later with reference to FIGS. The authentication image presentation unit 230 presents the authentication image (or authentication moving image) generated by the authentication image generation unit 220 to the client device 10.

  The communication unit 240 is an interface unit for performing communication with the client device 10. The service providing unit 250 provides a service to the client device 10 in response to a service request instruction received from the client device 10 when the authentication by the authentication unit 210 is successful. The control unit 260 includes the authentication unit 210, the authentication image generation unit (authentication video generation unit) 220, the authentication image presentation unit (authentication video presentation unit) 230, the communication unit 240, and the service provision unit 250. Various controls of the server device 20 are performed.

(Operation example of authentication system)
FIG. 3 is a flowchart illustrating an example of the operation of the authentication system according to the first embodiment. Here, the server device 20 performs an authentication operation to determine whether or not the user of the client device 10 is an actual person.

  First, the client device 10 requests authentication from the server device 20 (S1). Here, the user makes an authentication request to the server device 20 via the client device 10. It may be a service provision request for receiving the service provision.

  In step S2, the server device 20 presents an authentication image (or authentication moving image) to the client device 10 (S2). Here, the authentication image generation unit 220 first generates an authentication image (or an authentication moving image) (for example, an image in which an image corresponding to characters and / or symbols is drawn as shown in FIG. 6). Next, the authentication image presentation unit 230 presents the authentication image generated by the authentication image generation unit 220 to the client device 20. Subsequently, the display unit 120 of the client device 10 displays the authentication image.

  In step S3, the client apparatus 10 transmits a test result to the server apparatus 20 (S3). Here, the user reads the characters and / or symbols drawn on the authentication image presented in step S <b> 2, and inputs test result information such as the read characters and / or symbols and character strings using the input unit 110. Information on the test result input by the input unit 110 is transmitted to the server device 20.

  Proceeding to step S4, the server device 20 determines whether or not the test result information received at step S3 is correct (S4). Here, the authentication unit 210 performs determination (authentication) by comparing whether or not the test result information received in step S3 is equal to the character and / or symbol in the authentication image presented in step S2. If determined to be correct (YES in S4), the process proceeds to step S5. If it is determined that it is wrong (NO in S4), the process returns to step S2.

  In step S5, the server apparatus 20 displays an authentication screen on the client apparatus 10 (S5). Here, for example, an authentication screen for authenticating a user consisting of a user name (character string for user identification) input and a password input form is presented to prompt the user for authentication.

  In step S6, the client device 10 transmits the user name and password to the server device 20 (S6). Here, the user inputs the user name and password through the input unit 110 on the authentication screen presented in step S5. Information on the user name and password input by the input unit 110 is transmitted to the server device 20.

  Proceeding to step S7, the server device 20 determines whether or not the user is a regular user based on the user name and password information received at step S6 (S7). Here, the authentication unit 210 performs determination (authentication) by comparing the user name and password information received in step S6 with user information managed by a storage unit (not shown).

  If it is determined that the user is an authorized user (YES in S7), for example, the service providing unit 250 starts providing a service such as displaying a content posting form. If a service provision request is received in step S1, service provision may be started in response to the received service provision request. If it is determined that the user is not an authorized user (NO in S7), the process returns to step S5.

  Through the processing described above, the server device 20 performs an authentication operation to determine (authenticate) whether or not the user of the client device 10 is an actual person.

  Note that the order of the processes shown in steps S2 to S4 and the processes shown in steps S5 to S7 may be reversed. If the request from the client device 10 to the server device 20 is acquisition of an account to the server device 20, only the processing shown in steps S11 to S14 is performed as shown in FIG. You may start. FIG. 4 is a flowchart illustrating another operation example of the authentication system according to the first embodiment. The processes from step S11 to S14 are the same as steps S1 to S4 in FIG.

(Authentication using conventional authentication images)
Next, a conventional authentication operation (visual anti-robot test) will be described with reference to FIGS.

  FIG. 5 is an example of an authentication image used in a conventional authentication system. The image shown in FIG. 5 is an authentication image presented from the server apparatus 20 to the client apparatus 10 in step S12 of FIG.

  The image shown in FIG. 5 can be read as “NkpGJN” by a human. However, in order for a computer program to recognize characters and symbols rasterized as an image as shown in FIG. 5, it must have a special character recognition function such as OCR. Furthermore, it has been difficult to recognize characters and / or symbols that are distorted or obscured as shown in FIG. 5 using OCR. That is, if the client device 10 side is a so-called “bot”, it must have at least an OCR function. Further, even if the client device 10 has the OCR function, it is difficult to read the characters and / or symbols that are distorted or obscured as shown in FIG. OCR with more advanced learning is required.

  This is technically very difficult and costly, so it is very difficult to implement such things indiscriminately, in large quantities and at low cost using a computer program.

  In this way, in the conventional authentication system (visual anti-robot test system), it is determined whether the user of the client device 10 is an actual person or an automated computer program. However, in view of the recent advancement of OCR technology and cost reduction, such a method is no longer a safe method.

  Hereinafter, each example of the authentication image (or authentication moving image) in the first embodiment that solves such a problem will be described with reference to FIGS. The authentication image (or authentication moving image) shown in each example is provided with an image corresponding to a character and / or symbol on the background. At this time, there is no edge due to an image density difference between the background and the image corresponding to the character and / or symbol.

(First example of authentication image)
A first example of the authentication image according to the first embodiment will be described with reference to FIGS. 6 and 7. The image shown in FIG. 6 is a first example of an authentication image presented from the server device 20 to the client device 10 in step S2 of FIG.

  The image shown in FIG. 6 is different from the first texture on the background made of the first texture, and is provided with authentication information made of the second texture that forms an image corresponding to characters and / or symbols. It is an image.

  The first texture is an image in which white and black diagonal lines having a predetermined angle are alternately drawn in the example of FIG. The second texture is an image in which the diagonal line indicated by the first texture is a dotted line in the example of FIG.

  The image corresponding to the character and / or symbol is expressed by a combination of a plurality of arbitrarily selected characters and / or symbols. Further, the selected character and / or symbol may be different every session (each operation shown in FIG. 3).

  The image shown in FIG. 6 can be read as “ABCDEF” by a human. That is, a human can accurately recognize characters and / or symbols from such an image.

  However, when the first derivative of luminance as obtained in a normal OCR is acquired by a computer program, only the edge of the texture itself is extracted as shown in FIG. Therefore, an edge between the character and / or symbol and the background for separating the character and / or symbol from the background cannot be extracted.

  Therefore, in order for the “bot” to recognize this, not only OCR is required but also more complicated image processing is required as preprocessing. In addition, since image processing for such preprocessing requires a large-capacity memory and a high-speed CPU, the cost for implementing this inevitably increases.

  As described above, both technical difficulty and cost for passing the authentication using the authentication image as exemplified in the first example of the authentication image are increased. Therefore, those who try to do nuisance using “bots” need higher performance hardware or have to reduce the number of nuisances per unit time. Implementation becomes less realistic.

(Second example of authentication image)
A second example of the authentication image according to the first embodiment will be described with reference to FIG. The image shown in FIG. 8 is a second example of the authentication image presented from the server device 20 to the client device 10 in step S2 of FIG. 3, for example.

  The image shown in FIG. 8 is different from the first texture on the background made of the first texture, and is for authentication made of the second texture that forms an image corresponding to at least one character and / or symbol. It is an image provided with information.

  The first texture is an image in which white and black oblique lines having a predetermined angle are alternately drawn in the example of FIG. In the example of FIG. 8, the second texture is an image in which white and black diagonal lines having different angles from the diagonal lines indicated by the first texture are alternately drawn.

  Here, the difference between the first texture and the second texture is the form (direction in this example) of each texture. Further, the average density value (luminance) of the image corresponding to the characters and / or symbols is equal to or substantially equal to the average density value (luminance) of the background portion.

  The image corresponding to the character and / or symbol is expressed by a combination of a plurality of arbitrarily selected characters and / or symbols. Further, the selected character and / or symbol may be different every session (each operation shown in FIG. 3).

  The image shown in FIG. 8 can be read as “ABCD” by a human. That is, a human can accurately recognize characters and / or symbols from such an image.

  However, in addition to the reason described in the first example of the authentication image, the image corresponding to the character and / or the symbol and the image corresponding to the character and / or the symbol based on the difference in the average density of the background portion It is difficult to detect an edge with the background.

  Therefore, in order for “bots” to recognize this, it is necessary to perform a convolution operation of a second-order differential filter that requires a larger memory and a larger number of operations as a normal OCR pre-processing, which is inevitable. In addition, the cost to implement this also increases.

  As described above, both technical difficulty and cost for passing the authentication using the authentication image exemplified in the second example of the authentication image are increased. Therefore, those who try to do nuisance using “bots” need higher performance hardware or have to reduce the number of nuisances per unit time. Implementation becomes less realistic.

(Example of authentication video)
An example of the authentication moving image according to the first embodiment will be described with reference to FIGS.

  The image shown in FIG. 9 is an example of an image (authentication image) that constitutes an authentication moving image presented from the server device 20 to the client device 10 in step S2 of FIG.

  The background area and foreground area of the authentication image shown in FIG. 9A are images made of textures composed of random dots with a white / black pixel ratio of 1: 1.

  The foreground area of the authentication image is an image cut out in the form of a character and / or symbol area using the mask data shown in FIG. 9B from the image shown in FIG. An image of the foreground area is shown in FIG. The background area of the authentication image is cut out in the form of a character and / or symbol area from the image shown in FIG. 9A using mask data obtained by inverting the mask data as shown in FIG. 9B. It is an image (the image of the clipped background area is shown in FIG. 10B).

  An authentication moving image is generated in which the positional relationship between the background region and foreground region of the authentication image generated in this manner changes with time. For example, in the example of the moving image for authentication, the texture in the foreground area moves in parallel while maintaining the positional relationship of dots in a predetermined direction over time as shown in FIG. The moving direction may be any direction. The authentication moving image in the example of the authentication moving image is configured by an authentication image in which the foreground region is displayed on the background region.

  Such an authentication video is random dots at a predetermined time, but since humans can detect edges only by motion perception without any other visual information, humans can detect this over time. When observed, characters and / or symbols can be recognized.

  However, in order for the “bot” to recognize this, it is necessary to calculate temporal differentiation or difference from the video as normal OCR preprocessing, which requires a large amount of memory and a high-speed CPU. Inevitably, the cost of doing this also increases.

  As described above, both technical difficulty and cost for passing authentication using the authentication moving image as exemplified in the example of the authentication moving image increase. Therefore, those who try to do nuisance using “bots” need higher performance hardware or have to reduce the number of nuisances per unit time. Implementation becomes less realistic.

  In the example of the authentication moving image, the texture constituted by the random dots cut out by the mask data as shown in FIG. 9B has a sufficiently wide area in advance for the movement of the foreground area, or the foreground area. The texture that is deficient at the rear end of the movement is generated each time, but this is not a limitation. The moving direction may be reversed before the shortage occurs due to the movement of the foreground area.

  Further, in the example of the moving image for authentication, an example in which the foreground area moves in parallel while maintaining the positional relationship of dots in a predetermined direction over time is illustrated, but the present invention is not limited thereto. The background region may move in parallel while maintaining the positional relationship of dots in a predetermined direction over time.

(Another example of video for authentication)
Another example of the authentication moving image according to the first embodiment will be described with reference to FIG.

  The image shown in FIG. 11 is an example of an image (authentication image) that constitutes an authentication moving image presented from the server device 20 to the client device 10 in step S2 of FIG.

  The foreground area of the authentication image is an image cut out in the form of a character and / or symbol area using the mask data shown in FIG. 9B from the image shown in FIG. An image of the foreground area is shown in FIG. The background area of the authentication image is cut out in the form of a character and / or symbol area from the image shown in FIG. 9A using mask data obtained by inverting the mask data as shown in FIG. 9B. It is an image (the image of the clipped background area is shown in FIG. 11B).

  The positional relationship between the background area and foreground area of the authentication image generated in this way changes with time. For example, in the example of the authentication moving image, the textures of the foreground area and the background area are changed over time while maintaining the positional relationship of the dots in different predetermined directions as shown in FIGS. Move in parallel. As long as the moving directions of the textures of the foreground area and the background area are different directions, any direction may be used.

  The authentication moving image in the example of the authentication moving image is configured by an authentication image in which such a foreground region is displayed over the background region.

  Such an authentication video is random dots at a predetermined time, but since humans can detect edges only by motion perception without any other visual information, humans can detect this over time. When observed, characters and / or symbols can be recognized.

  Furthermore, unlike the authentication video example described above, the texture of both the foreground area and the background area moves in different directions, so the difference in these movements increases the number of clues that humans need for edge recognition. This also has the advantage that the recognition of characters and symbol strings becomes easier.

  However, even if the “bot” tries to recognize this and calculates a temporal derivative or difference from the moving image, the dot pattern is random, so these calculation results also form a random dot image, It is impossible to detect an edge between both regions only from time differentiation or difference.

  Therefore, in order to recognize this with a “bot”, it is necessary to detect the corresponding points of the pattern over time as normal OCR preprocessing, and to detect this movement direction. Inevitably increases the cost of implementing this.

  As described above, both technical difficulty and cost for passing authentication using the authentication moving image as exemplified in another example of the authentication moving image increase. Therefore, those who try to do nuisance using “bots” need higher performance hardware or have to reduce the number of nuisances per unit time. Implementation becomes less realistic.

  In another example of the authentication moving image, does the texture formed by the random dots cut out by the mask data as shown in FIG. 9B have a sufficiently wide area for the movement of the foreground area in advance? Textures that are insufficient at the rear end of the foreground area are generated each time, but this is not a limitation. The moving direction may be reversed before the shortage occurs due to the movement of the foreground area.

(Third example of authentication image)
A third example of the authentication image according to the first embodiment will be described with reference to FIGS. 12 and 13. The image shown in FIG. 12 is a third example of the authentication image presented from the server device 20 to the client device 10 in step S2 of FIG. 3, for example.

  The image shown in FIG. 12 is a random dot stereogram image in which an image corresponding to characters and / or symbols is embedded. The random dot stereogram image shown in FIG. 12 is an image of the background region shown in FIG. 13B with respect to the two background region images formed of the same first texture pattern shown in FIG. Unlike the image pair, the image pairs are formed by superimposing two pieces of authentication information composed of a second texture pattern that forms images corresponding to characters and / or symbols that differ only in relative positions within the image.

  The image corresponding to the character and / or symbol is expressed by a combination of a plurality of arbitrarily selected characters and / or symbols. Further, the selected character and / or symbol may be different every session (each operation shown in FIG. 3).

  The user can use the parallel method (observing the right image toward the right eye and the left image toward the left eye) with both eyes, or the intersection method (observing the left image toward the right eye with the left eye). In the example of FIG. 12, the character “A” is displayed on the back side of the background or by observing with an observation method called “observing the image on the right side”. It is possible to observe it by raising to the near side.

  This is because the human visual information processing system detects the binocular corresponding point from the input to the left and right eyes, in this case from the random dot stereogram image pair, and the character and / or symbol region having a relative position different from the background region Here, the parallax of the character region “A”, so-called binocular parallax, is detected and the fact that depth perception is established is used.

  In a random dot stereogram image having such a configuration, if only one of the images is used, it is simply a collection of random dots, and it is impossible to extract an image area corresponding to characters and / or symbols. It is.

  If the binocular parallax of the region of the image corresponding to the character and / or symbol, that is, if the difference in the relative position of each character and / or symbol in the image is small, even if a simple inter-image subtraction is performed between the image pairs, As shown in FIG. 13C, the character and symbol string regions partially overlap.

  Therefore, this method cannot correctly extract the edge of the image area corresponding to the character and / or symbol. If the “bot” tries to recognize this, an operation such as binocular corresponding point detection between image pairs is required as a normal OCR preprocessing. Therefore, since a large-capacity memory and a high-speed CPU are required, the cost for implementing this inevitably increases.

  As described above, both technical difficulty and cost for passing the authentication using the authentication image exemplified in the third example of the authentication image increase. Therefore, those who try to do nuisance using “bots” need higher performance hardware or have to reduce the number of nuisances per unit time. Implementation becomes less realistic.

  In the third example of the authentication image, a random dot stereogram image that requires two image pairs is illustrated as an example of the authentication image, but the present invention is not limited to this case. For example, a single image random dot stereogram image that enables binocular stereoscopic vision with one image, a stereogram image using a specific texture that is meaningful instead of random dots, or the like may be used.

(Fourth example of authentication image)
A fourth example of the authentication image according to the first embodiment will be described with reference to FIGS. 14 and 15. The image shown in FIG. 14 is a fourth example of the authentication image presented from the server device 20 to the client device 10 in step S2 of FIG. 3, for example.

  The image shown in FIG. 14 is arranged on a background composed of a single color, and an object group of at least one color different from the background, and a part of the object group overlaps at least part of the same color as the background. It is an image which consists of an image corresponding to the character and / or symbol drawn by (1).

  The object group is a black circle image of a predetermined size in the example of FIG. The image corresponding to the characters and / or symbols is an image drawn in the same color as the white background in the example of FIG.

  The image corresponding to the character and / or symbol is expressed by a combination of a plurality of arbitrarily selected characters and / or symbols. Further, the selected character and / or symbol may be different every session (each operation shown in FIG. 3).

  The image shown in FIG. 14 can be read as “ABCD” by a human. That is, a human recognizes that a character string of the same color as the background is floating on the plane where the object is present from an image including such an area where no actual contour exists. It is possible to accurately guess and recognize characters and symbol strings. The contour perceived in this way is called a subjective contour.

  However, when a first derivative of luminance as obtained in a normal OCR is obtained by a computer program, incomplete character and / or symbol edges and object group edges are extracted as shown in FIG. Only. Therefore, characters and / or symbols cannot be recognized separately from the object group.

  Therefore, in order for the “bot” to recognize this, not only OCR is required but also more complicated image processing is required as preprocessing. In addition, since image processing for such preprocessing requires a large-capacity memory and a high-speed CPU, the cost for implementing this inevitably increases.

  As described above, both technical difficulty and cost for passing authentication using the authentication image exemplified in the fourth example of the authentication image increase. Therefore, those who try to do nuisance using “bots” need higher performance hardware or have to reduce the number of nuisances per unit time. Implementation becomes less realistic.

(Fifth example of authentication image)
A fifth example of the authentication image according to the first embodiment will be described with reference to FIG.

  The image shown in FIG. 16 is a fifth example of the authentication image presented from the server device 20 to the client device 10 in step S2 of FIG. 3, for example.

  The image shown in FIG. 16 includes an object group composed of line drawings composed of a color different from the background, characters drawn on the same color as the background, and / or a part of at least a part of the object group. It is an image consisting of an image corresponding to a symbol.

  The object group is a circular image composed of a black line drawing in the example of FIG. The image corresponding to the characters and / or symbols is an image drawn in the same color as the white background in the example of FIG.

  The image corresponding to the character and / or symbol is expressed by a combination of a plurality of arbitrarily selected characters and / or symbols. Further, the selected character and / or symbol may be different every session (each operation shown in FIG. 3).

  The image shown in FIG. 16 can be read as “ABCD” by a human. That is, a human can accurately recognize characters and / or symbols from such an image.

  However, for the reason described in the third example of the authentication image described above, in order for the “bot” to recognize this, a large-capacity memory and a large number of computations are required as normal OCR preprocessing. A convolution operation or the like of the second derivative filter must be performed, and the cost for implementing this inevitably increases.

  As described above, both technical difficulty and cost for passing the authentication using the authentication image as exemplified in the fifth example of the authentication image are increased. Therefore, those who try to do nuisance using “bots” need higher performance hardware or have to reduce the number of nuisances per unit time. Implementation becomes less realistic.

(Sixth example of authentication image)
A sixth example of the authentication image according to the first embodiment will be described with reference to FIG.

  The image shown in FIG. 17 is a sixth example of the authentication image presented from the server device 20 to the client device 10 in step S2 of FIG. 3, for example.

  The image shown in FIG. 17 is arranged on a background composed of a single color, and an object group composed of at least one kind of texture, and a part of the object group overlaps at least a part of the same color as the background. It is an image which consists of an image corresponding to the character and / or symbol drawn by (1).

  In the example of FIG. 17, the object group is a circular image composed of textures drawn so that black pixels and white pixels are alternately adjacent to each other. The image corresponding to the characters and / or symbols is an image drawn in the same color as the white background in the example of FIG.

  The image corresponding to the character and / or symbol is expressed by a combination of a plurality of arbitrarily selected characters and / or symbols. Further, the selected character and / or symbol may be different every session (each operation shown in FIG. 3).

  The image shown in FIG. 17 can be read as “ABCD” by a human. That is, a human can accurately recognize characters and / or symbols from such an image.

  However, in addition to the reason described in the third example of the authentication image, the image corresponding to the character and / or the symbol and the image corresponding to the character and / or the symbol based on the difference in the average density of the background portion It is difficult to detect an edge with the background.

  Therefore, in order for “bots” to recognize this, it is necessary to perform a convolution operation of a second-order differential filter that requires a larger memory and a larger number of operations as a normal OCR pre-processing, which is inevitable. In addition, the cost to implement this also increases.

  As described above, both technical difficulty and cost for passing the authentication using the authentication image as exemplified in the sixth example of the authentication image are increased. Therefore, those who try to do nuisance using “bots” need higher performance hardware or have to reduce the number of nuisances per unit time. Implementation becomes less realistic.

(Seventh example of authentication image)
A seventh example of the authentication image according to the first embodiment will be described with reference to FIG.

  The image shown in FIG. 18 is a seventh example of the authentication image presented from the server device 20 to the client device 10 in step S2 of FIG.

  The image shown in FIG. 18 is arranged on a background made of a first texture, and an object group filled with at least one color and a part of the object group are arranged on at least a part of the object group. And an image composed of at least one character and / or symbol drawn with the same texture as the background.

  The object group is a circle image made of black in the example of FIG. The image corresponding to the characters and / or symbols is an image drawn with a texture drawn so that black pixels and white pixels are alternately adjacent in the example of FIG.

  The image corresponding to the character and / or symbol is expressed by a combination of a plurality of arbitrarily selected characters and / or symbols. Further, the selected character and / or symbol may be different every session (each operation shown in FIG. 3).

  The image shown in FIG. 18 can be read as “ABCD” by a human. That is, a human can accurately recognize characters and / or symbols from such an image.

  However, for the reason described in the above-described third example of the authentication image, in order for the “bot” to recognize this, a larger capacity memory and a larger number of operations are required as pre-processing of normal OCR. A convolution operation or the like of the second derivative filter must be performed, and the cost for implementing this inevitably increases.

  As described above, both technical difficulty and cost for passing the authentication using the authentication image as exemplified in the sixth example of the authentication image are increased. Therefore, those who try to do nuisance using “bots” need higher performance hardware or have to reduce the number of nuisances per unit time. Implementation becomes less realistic.

(Eighth example of authentication image)
An eighth example of the authentication image according to the first embodiment will be described with reference to FIG.

  The image shown in FIG. 19 is an eighth example of the authentication image presented from the server device 20 to the client device 10 in step S2 of FIG.

  The image shown in FIG. 19 is arranged on a background composed of a first texture, and an object group composed of at least one kind of texture (here, the second texture) different from the first texture; It is an image made up of images corresponding to characters and / or symbols drawn with the same first texture as the background, which are arranged so as to overlap at least a part of these object groups.

  The first texture is an image in which white and black horizontal lines (straight lines and broken lines) are alternately drawn in the example of FIG. The second texture is an image in which white and black oblique lines having a predetermined angle are alternately drawn in the example of FIG.

  The object group is a circular image composed of the second texture in the example of FIG. The image corresponding to the characters and / or symbols is an image made up of the first texture in the example of FIG.

  The image corresponding to the character and / or symbol is expressed by a combination of a plurality of arbitrarily selected characters and / or symbols. Further, the selected character and / or symbol may be different every session (each operation shown in FIG. 3).

  The image shown in FIG. 19 can be read as “ABCD” by a human. That is, a human can accurately recognize characters and / or symbols from such an image.

  However, for the reason described in the above-described third example of the authentication image, in order for the “bot” to recognize this, a larger capacity memory and a larger number of operations are required as pre-processing of normal OCR. A convolution operation or the like of the second derivative filter must be performed, and the cost for implementing this inevitably increases.

  As described above, both technical difficulty and cost for passing authentication using the authentication image as exemplified in the eighth example of the authentication image are increased. Therefore, those who try to do nuisance using “bots” need higher performance hardware or have to reduce the number of nuisances per unit time. Implementation becomes less realistic.

(Ninth example of authentication image)
A ninth example of the authentication image according to the first embodiment will be described with reference to FIG.

  The image shown in FIG. 20 is a ninth example of the authentication image presented from the server device 20 to the client device 10 in step S2 of FIG. 3, for example.

  The image shown in FIG. 20 is composed of images corresponding to dummy characters or symbols, for example, in the third to eighth examples of the authentication image. In the example of FIG. 20, the dummy character is “ZYXWVUTS”.

  The image corresponding to the dummy character or symbol is expressed by a combination of a plurality of arbitrarily selected characters and / or symbols. Further, the selected character and / or symbol may be different every session (each operation shown in FIG. 3).

  The image shown in FIG. 20 can be read as “ABC” by a human. That is, a human can accurately recognize characters and / or symbols from such an image.

  However, for the reason described in the above-described third example of the authentication image, in order for the “bot” to recognize this, a larger capacity memory and a larger number of operations are required as pre-processing of normal OCR. A convolution operation or the like of the second derivative filter must be performed, and the cost for implementing this inevitably increases.

  As described above, both the technical difficulty and the cost for passing authentication using the authentication image as exemplified in the ninth example of the authentication image are increased. Anyone who wants to do an action will need more sophisticated hardware or will have to reduce the number of nuisance actions per unit time, making the nuisance action less realistic.

  Furthermore, even if a “bot” using OCR or the like tries to recognize this image, it is not authentication information that does not have an explicit contour with respect to the background, but a dummy that is relatively easy to detect the contour with respect to the background. Are detected, and an obvious wrong answer is given (in the example of FIG. 20, for example, an answer starting with Z or V).

  For example, the server device 20 can register the client device 10 that transmits an obvious wrong answer in step S3 of FIG. 3 in an access prohibition list that prohibits access to the server device 20 thereafter. This makes it possible to take measures such as making access impossible.

(Tenth example of authentication image)
A tenth example of the authentication image according to the first embodiment will be described with reference to FIG.

  FIG. 21A shows text information presented from the server device 20 to the client device 10 in step S2 of FIG. 3, for example.

  FIG. 21A shows text information in which each of characters and / or symbols (“A, B, C, D” in the example of FIG. 21A) is composed of a plurality of characters and / or symbols. Specifically, a plurality of spaces, arbitrary character symbol groups, and line feed groups are used, and these character symbol groups are regarded as constituent elements of other character symbols, and are generally called ASCII art. The server device 20 presents these to the client device 10 as text information rather than as images.

  Note that text information of characters and / or symbols is expressed by a combination of a plurality of arbitrarily selected characters and / or symbols. Further, the selected character and / or symbol may be different every session (each operation shown in FIG. 3).

  The text information shown in FIG. 21A can be read as “ABCD” by a human. That is, a human can accurately recognize characters and / or symbols from such an image.

  When a human observes the text information presented in this way, it recognizes the character symbol group composed of these by the perceptual mechanism called grouping, and in this case "ABCD". can do.

  However, it is very difficult for “bots” to analyze the text information presented in this way, once these texts are rasterized as images, and more memory and much more as normal OCR preprocessing. Therefore, the convolution operation of the secondary differential filter that requires the number of operations is necessary, and the cost for implementing this inevitably increases.

  In addition, if it is a “bot” that can only perform processing with lower accuracy, it is not “ABCD”, which is originally required to be identified, but an element that constitutes these characters and / or symbols. Since the character and / or symbol “AOPQR” is recognized, it is very easy to identify whether or not the server device 20 is “bot”.

  For example, the server device 20 can register the client device 10 that transmits an obvious wrong answer in step S3 of FIG. 3 in an access prohibition list that prohibits access to the server device 20 thereafter. This makes it possible to take measures such as making access impossible.

  FIG. 21B shows an authentication image presented from the server device 20 to the client device 10 in step S2 of FIG. 3, for example.

  The authentication image shown in FIG. 21 (b) is the same as FIG. 21 (a) except that the authentication image is not text information but image information, and a description thereof will be omitted here.

(Modification)
As described above, the present invention has been described based on the embodiment. However, the authentication image (or the authentication moving image) shown in each example of the above-described authentication image (or the authentication moving image) has characters and / or characters on the background. Alternatively, an image corresponding to the symbol is provided. At this time, there is no edge due to the image density difference between the background and the image corresponding to the character and / or symbol.

  For this reason, even if it is a human being, the perception of the edge becomes unstable, so that misrecognition increases compared with the case of recognizing normal characters and / or symbols. Therefore, as a modification of the present embodiment, in the authentication image presented by the server device 20, the alphabet uppercase “I”, the alphabet lowercase “l”, the number “1”, and the alphabet lowercase “o” It is not necessary to use characters and / or symbols that are set to be easily confused by humans, such as the uppercase alphabet “O”, the number “0”, the symbol “:”, and the symbol “;”. Thereby, human misrecognition can be reduced.

  In addition, even if each example of the authentication image described above is used, if the authentication operation (visual anti-robot test) is performed by the same method every time, the person who intends to carry out the nuisance acts will use the “bot” dedicated to the authentication operation. May be created to pass the authentication operation. The cost of creating such “bots” can fall to an acceptable level, especially for sites with a large number of visits every day.

  Accordingly, as a modification of the first embodiment, any one of the above-described authentication images is randomly selected as the authentication image presented by the server device 20 for each session (each operation illustrated in FIG. 3). A process is provided. As a result, it is possible to increase the difficulty and cost of creating and executing the “bot”, making it difficult to execute the nuisance, and further improving the security.

  Further, as a modification of the first embodiment, the authentication images described above as the authentication images presented by the server device 20 for each session (each operation shown in FIG. 3) are arranged in a random order, for example. A process (step) to present is provided. In this case, the character or symbol included in each authentication image may be one character at a time, and the burden on the authorized user is almost the same as when using any one type, and the technology required by the “bot” Only the difficulty and cost increase. This makes it difficult to perform nuisance and can further improve security.

[Second Embodiment]
Hereinafter, a second embodiment of the present invention will be described with reference to FIGS.

  The system configuration, functional configuration, and operation of the authentication system according to the second embodiment are the same as those of the first embodiment (see FIGS. 1, 2, and 3), and the description thereof is omitted here. A supplementary description will be given of the authentication image presentation unit (authentication video presentation unit) 230 in FIG.

  The authentication image presenting unit (authentication moving image presenting unit) 230 according to the first embodiment presented the authentication image (or authentication moving image) generated by the authentication image generating unit 220. Here, in addition to the authentication image (or authentication moving image), as shown in FIG. 22 or FIG. 26 to be described later, selection of a list box, a check box, or the like that prompts selection according to the presented authentication image Present the screen as a presentation screen. Examples of these selection screens will be described later with reference to FIGS. In addition, according to the second embodiment, an example in which the selection screen is presented in addition to the authentication moving image will be described, but the selection screen may be presented in addition to the authentication image.

(First example of authentication video presentation screen)
A first example of the authentication moving image presentation screen according to the second embodiment will be described with reference to FIG.

  FIG. 22 is a display example of a screen presented from the server device 20 to the client device 10 in step S2 of FIG. 3, for example.

  The screen display content shown in FIG. 22 is to transmit to the server device 20 the authentication moving image portion 1 in which the authentication moving image is presented, the select box 2 that lists options for selection by the user, and the user selection in the select box 2. The transmission button 3 is configured.

  An example of the authentication moving image presented in the authentication moving image unit 1 will be described later with reference to FIGS. On the screen shown in FIG. 22, an option indicating the type of exercise perceived by the user observing the authentication moving image unit 1 is selected from the list of the select box 2 as a test result. Further, when the transmission button 3 is pressed, the selected test result is transmitted to the server device 20 by the HTTP POST method or the like. The server device 20 performs authentication by judging whether or not the test result is correct by comparing the received test result with the presented content of the authentication moving image.

  An example of the authentication moving image presented by the authentication moving image unit 1 will be described below.

(First example of authentication video)
FIG. 23 is a first example of an authentication moving image according to the second embodiment. The image shown in FIG. 23 is a first example of an image (authentication image) that forms an authentication moving image presented from the server device 20 to the client device 10 in step S2 of FIG. 3, for example. FIG. 24 is a diagram for supplementary explanation of FIG.

  FIG. 23 shows an example of a moving image that is composed of a background and a point cloud that moves on the background, and is perceived as a human walking by human observation. The point cloud in each image corresponds to a characteristic part such as the head, shoulder, elbow, wrist, waist, foot, ankle during human walking, and each point corresponding to the position on the human body. The points move in accordance with the movement of the human walking while maintaining an appropriate physical distance.

  By continuously presenting a series of these images as moving images, the upper row in FIG. 23 is sequentially presented from left to right and then the lower row in order from left to right. As shown in FIG. It is perceived as a connected body in the sense that it is perceived as a walking human being.

  This is thought to be due to a perceptual mechanism acquired in order to quickly recognize other human moving people or other living organisms.

  However, it is very difficult for a computer program to determine, for example, a biological motion moving image as shown in FIG. Moreover, even if a computer algorithm capable of making such a determination is developed and can be implemented as a program, very complicated processing such as grouping and identification of moving point clouds is required. Moreover, since such a process requires a large-capacity memory and a high-speed CPU, the cost for implementing this inevitably increases.

  In this way, technical difficulty and cost for passing the authentication test as exemplified in the example of the video for authentication increase together, so those who try to do nuisance using “bots” The implementation of nuisances becomes less realistic, requiring higher performance hardware or reducing the number of nuisances per unit time.

  In the example of the video for authentication, biological motion perception that is perceived as a human walking or jumping by an observing human is exemplified as an example, but instead of these, other exercises such as throwing and kicking things May be a moving image perceived as biological motion.

  As described above, the authentication system according to the present embodiment uses a moving image that is composed of a point cloud that moves on the background and that allows a human observer to perceive biological motion. It is characterized by discriminating whether or not the user is a human.

  As a result, it is possible to make it more difficult to perform a nuisance action using a computer program that automatically exchanges data with a server in a service on a computer network.

(Second example of authentication video)
FIG. 25 is a second example of the authentication moving image according to the second embodiment. The image shown in FIG. 25 is a second example of an image (authentication image) that constitutes an authentication moving image presented from the server device 20 to the client device 10 in step S2 of FIG. 3, for example.

  FIG. 25 is a diagram in which a biological motion moving image that can be perceived as a human who jumps while opening both hands is divided in time series. Actually, if we focus on each point of these point clouds, they move only irregularly, but our visual mechanism perceives the movement of each point for the first time by associating it with the movement of other points. It is perception. This phenomenon is called biological motion perception. This is thought to be due to a perceptual mechanism acquired in order to quickly recognize other human moving people or other living organisms.

(Second example of authentication video presentation screen)
Next, a second example of the authentication moving image presentation screen according to the second embodiment will be described with reference to FIG. FIG. 26 is a display example of a screen presented from the server device 20 to the client device 10 in step S2 of FIG. 3, for example.

  The screen display content shown in FIG. 26 is for selection by a user provided in each of the authentication moving image units 4, 5, 6, and the authentication moving image units 4, 5, 6 where a plurality of authentication moving images are presented. The check box 7 includes a transmission button 8 for transmitting the user selection in the check box 7 to the server device 20.

  An example of the authentication moving image presented in the authentication moving image units 4, 5, and 6 will be described later with reference to FIGS. On the screen shown in FIG. 26, any one type (or a plurality) of authentication moving image portions in which a moving image in which motion is perceived among the moving images displayed in the authentication moving image portions 4, 5, and 6 are displayed. An instruction is given by text or voice so as to select. A moving image is a moving image perceived as a human being walking, for example. At this time, a biological motion moving image perceived as a walking human is randomly displayed at any one (or a plurality of) positions in the authentication moving image portions 4, 5, 6. However, when two or more moving images in which the same type of motion is perceived are presented, the perceived human size and motion speed may be different.

  Each moving image is associated with a check box 7. In the client device 10, check boxes below all moving images that are perceived as a human being walking are checked. Further, when the transmission button 8 is pressed, the selected test result is transmitted to the server device 20 by the HTTP POST method or the like. The server device 20 performs authentication by judging whether or not the test result is correct by comparing the received test result with the presented content of the authentication moving image.

  By the way, it is very difficult to determine the type of motion perceived by biological motion in a computer program. Moreover, even if a computer algorithm capable of making such a determination is developed and can be implemented as a program, very complicated processing such as grouping and identification of moving point clouds is required. Moreover, since such a process requires a large-capacity memory and a high-speed CPU, the cost for implementing this inevitably increases.

  As described above, since both technical difficulty and cost for passing the authentication test as exemplified in the example of presenting the authentication video increase, those who try to perform nuisance using “bots”. Will require higher performance hardware or will be forced to reduce the number of nuisances per unit time, making nuisance practices less realistic.

  In the present example of presenting the moving image for authentication, the description has been given assuming that the number of moving images to be presented is three. The more moving images to present, the better. However, since this is in a trade-off relationship with the time required for presentation, the number is determined in consideration of the importance of the system to be authenticated, the degree of risk and operability. Shall.

(Third example of authentication video)
FIG. 27 is a third example of the authentication moving image according to the second embodiment. The image illustrated in FIG. 27 is a third example of an image (authentication image) included in the authentication moving image presented from the server device 20 to the client device 10 in step S2 of FIG.

  FIG. 27 shows an example of a moving image that is composed of a background and a point cloud that moves on the background, and is perceived as an animal that moves by being observed by a human (FIG. 27 is an example of a feline animal). The point cloud in each image corresponds to a characteristic part such as the head, shoulder, elbow, wrist, waist, foot, and ankle of the moving animal, and each point corresponding to the position on the body of the moving animal. The point moves in response to the movement of the animal moving at an appropriate physical distance.

  A series of these images as moving images, the upper row in FIG. 27 is continuously presented from left to right, and the lower row is successively presented from left to right. It is perceived as the body of an animal, and it is perceived as a walking human by a human being who observes it.

  The moving image is a moving image that can be perceived as biological motion, but can be perceived as a person whose point cloud moves when observed by a person as illustrated in FIG. 23 and FIG. A moving image and a moving image that is perceived as a moving animal when observed by a human, as illustrated in FIG. 27 in a time-series manner, are randomly displayed at positions 4, 5, and 6.

  In this way, biological motion perception is valid not only for moving humans but also for animals. As mentioned above, this is thought to be because biological motion perception is a perceptual mechanism acquired in order to quickly recognize other people who we move or other living organisms.

  On the screen shown in FIG. 26, any one type (or a plurality) of authentication moving image portions in which a moving image in which motion is perceived among the moving images displayed in the authentication moving image portions 4, 5, and 6 are displayed. An instruction is given by text or voice so as to select. At this time, the biological motion moving image perceived as a moving human is randomly displayed at one or more positions in the authentication moving image parts 4, 5, and 6, and the biological motion of the animal is displayed at the other positions. A moving image is presented. However, in the case where two or more moving images in which the same type of creature including human beings is perceived are presented, the size of the perceived creature, the movement speed, and the like may be different.

  As described above, in the authentication system 1 according to the second embodiment, a user uses a moving image that is composed of a point cloud that moves on the background and that allows a human observer to perceive biological motion. It is characterized by distinguishing the kind of organism (or movement) perceived by the human.

  As a result, it is possible to make it more difficult to perform a nuisance action using a computer program that automatically exchanges data with a server in a service on a computer network.

(Fourth example of authentication video)
FIG. 28 is a fourth example of the authentication moving image according to the second embodiment. The image shown in FIG. 28 is a fourth example of an image (authentication image) that constitutes the authentication moving image presented from the server device 20 to the client device 10 in step S2 of FIG. 3, for example.

  In FIG. 28, a moving image that is composed of a background and a point cloud that moves on the background and that can be perceived by biological motion, and that cannot be perceived by biological motion (that is, perceived as an animal that moves by being observed by humans). An example of a moving image (moving image that cannot be perceived in FIG. 28) is shown. Since the point cloud in each image moves randomly, it cannot perceive biological motion. Such moving images that cannot be perceived by biological motion are randomly presented to the authentication moving image portions 4, 5, and 6 in FIG. 26 for each authentication.

  On the screen shown in FIG. 26, any one type (or a plurality) of authentication moving image portions in which a moving image in which motion is perceived among the moving images displayed in the authentication moving image portions 4, 5, and 6 are displayed. An instruction is given by text or voice so as to select. At this time, the biological motion moving image is randomly displayed at one or more positions in the authentication moving image portions 4, 5, 6. However, when two or more moving images in which the same type of motion is perceived are presented, the perceived human size and motion speed may be different. In addition, when two or more moving images in which the same type of creature including human beings is perceived are presented, the size of the perceived creature, the motion speed, and the like may be different from each other.

(Modification of the authentication video presented by the authentication video part)
As described above, examples of authentication moving images have been described with reference to FIGS. 23, 25, 27, 28, and the like, but modifications of images (authentication images) constituting the authentication moving images will be described.

  The authentication moving image (or each authentication image constituting the authentication moving image) may be composed of only two colors of the background color and the point cloud. By adopting such a configuration, when compressing these moving images, it is possible to employ an LZW compression method such as that employed in animated GIFs, for example.

  In addition, since the authentication moving image has a very small area ratio of the point group with respect to the background, it is possible to realize a high speed and a very high compression rate. This is because in the LZW compression method employed in GIF, the compression rate of the image increases as the same color continues.

  As described above, the modification of the authentication moving image is characterized in that the moving image is composed of only two colors, that is, the color constituting the background and the color constituting the point group.

  This makes it more difficult to perform nuisance using a computer program that automatically communicates with a server in a service on a computer network, and allows the use data size to be reduced.

[Third Embodiment]
Hereinafter, a third embodiment of the present invention will be described with reference to FIGS.

  Since the system configuration and functional configuration of the authentication system according to the third embodiment are the same as those of the first embodiment (see FIGS. 1 and 2), description thereof is omitted here. As for the system configuration, a system configuration shown in FIG. 35 described later can be adopted. Further, the functional configuration will be supplementarily described with respect to the authentication image presentation unit (authentication video presentation unit) 230. Since the operation is different from that of the first embodiment, it will be described later with reference to FIG.

  The authentication image presenting unit (authentication moving image presenting unit) 230 according to the first embodiment presented the authentication image (or authentication moving image) generated by the authentication image generating unit 220. Here, in addition to the authentication image (or authentication video), as shown in FIG. 29 to be described later, an answer screen is provided with an answer column that prompts the user to answer according to the presented authentication image. Present as a screen. In addition, according to the third embodiment, an example in which an answer screen is presented in addition to an authentication image will be described. However, an answer screen may be presented in addition to an authentication video.

(Example of authentication image presentation screen)
An example of the authentication moving image presentation screen according to the third embodiment will be described with reference to FIG.

  FIG. 29 is a display example of a screen presented from the server device 20 to the client device 10 in step S22 of FIG. 30, for example.

  The screen display content shown in FIG. 29 is based on the authentication image portions 101 and 102 on which a plurality (two in this case) of authentication images are presented, and the authentication images presented on the respective authentication image portions 101 and 102. It consists of answer fields 103 and 104 for the user to answer.

  The authentication image presented in the authentication image unit 101 is information indicating an object name (for example, a man, a car, a building, etc.) included in the authentication image and a scene (for example, a suburb, winter, etc.) (Hereinafter, the information associated with the image for authentication is referred to as “tag information” or simply “tag”) selected at random from an image group (hereinafter referred to as “image group 1”). On the other hand, the authentication image presented in the authentication image unit 102 is an image group in which the tag information of the authentication image is not known (hereinafter referred to as “image group 2”). Image) such as one photographic image selected at random.

  On the screen shown in FIG. 29, tag information that is more appropriate for the user who observed the authentication image portions 101 and 102 is entered in the answer columns 103 and 104. Furthermore, when the transmission button 105 is pressed, the response contents (test results) in the response fields 103 and 104 are transmitted to the server device 20 by the HTTP POST method or the like. The server device 20 performs authentication by comparing the response content in the response field 103 in the received response content with the tag information given in association with the images belonging to the image group 1 in advance. Specifically, the correct answer rate indicating how many pieces of tag information previously given to the authentication image presented in the authentication image unit 101 are included in the transmitted response information is calculated. When the correct answer rate is a predetermined threshold (for example, 40% to 50%) or more, authentication is performed to determine that the user is a human. Hereinafter, these operations will be described in more detail with reference to FIG.

(Operation example of authentication system)
FIG. 30 is a flowchart illustrating an example of the operation of the authentication system according to the third embodiment. Here, the server device 20 performs an authentication operation to determine whether or not the user of the client device 10 is an actual person.

  First, the client device 10 requests authentication from the server device 20 (S21). Here, the user makes an authentication request to the server device 20 via the client device 10. It may be a service provision request for receiving the service provision.

  In step S22, the server device 20 presents an authentication image (or authentication moving image) to the client device 10 (S22). Here, first, the authentication image generation unit 220 belongs to an authentication image (or an authentication moving image) (an image belonging to the image group 1 and an image group 2 presented in each of the authentication image portions 101 and 102 in FIG. 29). Image). In particular, tag information given in advance to images belonging to the image group 1 is stored in a storage device such as an unillustrated image database (described later with reference to FIG. 35). Next, the authentication image presentation unit 230 presents the authentication image generated by the authentication image generation unit 220 to the client device 20. Further, an answer screen provided with an answer column for prompting the user to answer according to the presented authentication image is presented as a presentation screen. Subsequently, the display unit 120 of the client device 10 displays the authentication image and the presentation screen.

  In step S23, the client device 10 transmits response information to the server device 20 (S23). Here, the user uses the input unit 110 to input tag information that seems to be appropriate for the authentication image presented in step S22. The answer information input by the input unit 110 is transmitted to the server device 20.

  Proceeding to step S24, the server device 20 calculates a correct answer rate based on the answer information received at step S23 (S24). Here, the authentication unit 210 is included in the response in which the number of pieces of tag information previously assigned to the authentication image presented in the authentication image unit 101 is included in the response information received in step S23. Calculate the correct answer rate.

  Proceeding to step S25, the server device 20 determines whether or not the correct answer rate calculated in step S24 is equal to or greater than a predetermined threshold (S25). If it is determined that the value is equal to or greater than the predetermined threshold (YES in S25), the process proceeds to step S26. If it is determined that the value is less than the predetermined threshold (NO in S25), the process returns to step S22. The threshold here may be higher than the recognition accuracy (for example, 20% to 30%) by the state-of-the-art image recognition technology at that time, and may be set to 40% to 50%, for example.

  In step S26, the server device 20 displays an authentication screen on the client device 10 (S26). Here, for example, an authentication screen for authenticating a user consisting of a user name (character string for user identification) input and a password input form is presented to prompt the user for authentication.

  In step S27, the client device 10 transmits the user name and password to the server device 20 (S27). Here, the user inputs the user name and password through the input unit 110 on the authentication screen presented in step S26. Information on the user name and password input by the input unit 110 is transmitted to the server device 20.

  Proceeding to step S28, the server device 20 determines whether or not the user is a regular user based on the user name and password information received at step S27 (S28). Here, the authentication unit 210 performs determination (authentication) by comparing the user name and password information received in step S27 with user information managed by a storage unit (not shown).

  If it is determined that the user is an authorized user (YES in S28), for example, the service providing unit 250 starts providing a service such as displaying a content posting form. When a service provision request is received in step S21, service provision may be started in response to the received service provision request. If it is determined that the user is not an authorized user (NO in S28), the process returns to step S26.

  Through the processing described above, the server device 20 performs an authentication operation to determine (authenticate) whether or not the user of the client device 10 is an actual person.

  Note that the order of the processes shown in steps S22 to S25 and the processes shown in steps S26 to S28 may be reversed. If the request from the client device 10 to the server device 20 is an account acquisition to the server device 20, only the processing shown in steps S31 to S35 is performed as shown in FIG. 31, and then user registration is performed. You may start. FIG. 31 is a flowchart illustrating another operation example of the authentication system according to the third embodiment. The processes from step S31 to S35 are the same as steps S21 to S25 in FIG.

  Further, in this operation example, one photographic image is randomly selected and presented as an authentication image from each of the image group 1 in which a plurality of tag information is known and the image group 2 in which the tag information is not known. As shown, one or more arbitrary plural images may be selected and presented from both image groups.

  Thus, the authentication system according to this operation example presents at least two or more images on the same screen, and allows the user to answer an object included in the image or a scene that the image means. An authentication system for determining whether or not an image group 1 in which a plurality of words representing an object name included in an image or a scene represented by an image are known, and a word representing an object name included in the image or a scene represented by an image At least one or more images are randomly selected from each of the image groups 2 for which the user name is not known, and only the correct answer rate of the user's responses to the image groups for which multiple words representing object names and scenes are known It is characterized by making a determination based on the above.

  By having such a feature, it is possible to make it more difficult for a service on a computer network to perform a nuisance act using a computer program that automatically exchanges data with a server.

(Modification 1 of the operation example of the authentication system)
FIG. 32 is a flowchart illustrating a first modification of the operation of the authentication system according to the third embodiment. Here, a first modification of the operation example shown in FIG. 30 will be described. The processes from Steps S41 to S48 in FIG. 32 are the same as Steps S21 to S28 in FIG.

  If YES in step S48 (S48, YES), the process proceeds to step S49, and the server device 20 reclassifies the images belonging to the image group 2 presented in the authentication image unit 102 to the image group 1 (S49). Here, if the input user name and password are those of a legitimate user, it is determined that the reply information for the image presented on the authentication image unit 102 is also reliable to some extent. The reply information is associated as tag information and reclassified into the image group 1. In addition, service provision is started for the user.

  Such a configuration makes it more difficult to perform nuisance using a computer program that automatically communicates with the server, and the number of data in the image database can be increased sequentially. It is possible to easily construct an image database required in a system using photographic image content recognition.

  As described above, in the authentication system according to this operation example, when the user is determined to be a human, the answer information provided by the user to the image selected and presented from the image group 2 is set as tag information of the image, and the image is used as the authentication information. The image group 1 is classified.

  By having such a feature, in a service on a computer network, it is more difficult to carry out a nuisance act using a computer program for automatically exchanging with a server, and in a system using content recognition of a photographic image It is possible to facilitate the construction of the required image database.

(Modification 2 of the operation example of the authentication system)
FIG. 33 is a flowchart illustrating a second modification of the operation of the authentication system according to the third embodiment. Here, a second modification of the operation example shown in FIG. 30 will be described. The processes from Steps S51 to S59 in FIG. 33 are the same as Steps S41 to S49 in FIG.

  Simultaneously with the process related to step S59, the process proceeds to step S60, and the server device 20 associates response information for the image presented in the authentication image unit 101 with the image as tag information (S60). Here, if the input user name and password are those of a legitimate user, the answer information for the image presented on the authentication image unit 101 was not previously associated with the image as tag information. Since it is determined that the image is reliable to some extent, the response information is newly associated with the image as tag information.

  By adopting such a configuration, even if the user does not have an unintentional intention, the word given by the user by observing the image varies slightly depending on the subjectivity of the user, so that the user is erroneously determined not to be a human being. However, this misjudgment can be reduced.

  As described above, in the authentication system according to this operation example, when the user is determined to be a human being, the answer information given by the user to the image selected and presented from the image group 1 is not known before the test. The reply information is newly added as tag information of the image.

  By having such a feature, it is possible to improve accuracy when determining whether or not the user is a human.

(Modification 3 of the operation example of the authentication system)
FIG. 34 is a flowchart illustrating a third modification of the operation of the authentication system according to the third embodiment. Here, a third modification of the operation example shown in FIG. 30 will be described. The processes from step S61 to S70 in FIG. 34 are the same as steps S51 to S60 in FIG.

  When the process related to step S70 ends, the process proceeds to step S71, and the server apparatus 20 calculates the response rate for all tag information attached to the image presented on the authentication image unit 101 (S71). The response rate here is (the number of times the tag information is included in the response information for the image) / (the number of times the image is used for the test).

  Then, it progresses to step S72 and the server apparatus 20 re-selects a correct word (S72). Here, when the answer rate calculated in step S71 exceeds a predetermined threshold value such as 50%, for example, the correct word required when calculating the correct answer rate for the image from the next test using the tag information. And

  By adopting such a configuration, even if the user does not have an unintentional intention, the word given by the user by observing the image varies slightly depending on the subjectivity of the user, so that the user is erroneously determined not to be a human being. However, it is possible to select correct words based on a larger number of judgments, and to reduce such erroneous judgments.

  As described above, the authentication system according to this operation example calculates the response rate of the tag information given by the user determined to be a human for each image belonging to the image group 1 for each test. Based on the answer rate, a correct word required when calculating the correct answer rate for the image from the next test is selected.

  By having such a feature, it is possible to improve accuracy when determining whether or not the user is a human.

(Authentication system)
FIG. 35 is a diagram illustrating a system configuration example of an authentication system according to the third embodiment. In FIG. 35, the authentication system 1 is connected to the image database system 2 via a network or the like. The image database system 2 includes a database management system (hereinafter abbreviated as “DBMS”) 21 and a database 22 for managing various image data for authentication used for authentication.

  For example, as shown in FIG. 36, the data related to the authentication image managed on the database 22 includes an ID, an image name, an image file size, an image format, a registration date, a registrant name, and a registrant. IP address or host name (registered address) of the computer used for registration, tag information, number of times the image was used for authentication, number of times each tag information was answered during authentication, response rate for each tag information, and image ( Image data) as an element. When the user adds an image, the tag information may or may not be added. The ID of the image to which the tag information is assigned is not assigned tag information as image data belonging to the image group 1 The image ID is recorded as image data belonging to the image group 2 in image classification data having a structure as shown in FIG. 37, and is stored and managed on the database 22.

  With the system configuration described above, in the authentication system 1, when there is a new authentication request from the user, the image belonging to the image group 1 and the image group 2 belong to each other via a language that makes a request for a database such as SQL. An image request (image selection instruction) is made to the DBMS 21.

  Receiving the instruction for image selection, the DBMS 21 randomly selects one image ID from the image IDs belonging to the image group 1 using the image classification data shown in FIG. One image ID is selected at random, and images corresponding to all selected IDs are searched and extracted from the image data on the database 22, and the selection result is returned to the authentication system 1 together with the tag information. . The authentication system 1 uses the selection result for authentication as described in the above-described operation example.

  When the authentication system 1 determines that the user is a human and the user name and password are those of a regular user, it is determined that the reply information for the image presented on the authentication image unit 102 is also reliable to some extent. Therefore, a request for moving the image to the image group 1 and a request for registering the response information with respect to the image as tag information are made to the DBMS 21. Then, the DBMS 21 rewrites the image classification data (deletes the image from the image group 2 and adds the image to the image group 1), and adds the tag information that was answered to the image 2 at the time of authentication to the image of the image. In addition to the data, the number of times the image has been used for authentication is set to 1, the number of responses for each tag information is set to 1, and the response rate is set to 100% (see Modification 1 of the operation example).

  At the same time, among the reply information for the image presented on the authentication image unit 101, it is determined that the information that has not been previously associated with the image as tag information is also reliable to some extent. Then, the DBMS 21 is requested to register all tag information replied to the image in association with the tag information of the image. Then, the DBMS 21 adds 1 to the number of times of use of the image, adds 1 to the number of responses of each tag information that was known before the test in the response information at the time of authentication, and is not known before the test. The missing tag information is newly added to the image data of the image, and the number of answers is set to 1. Furthermore, the response rate is recalculated for all the tags registered at this time, and is stored in the image data (refer to Modification Examples 2 and 3 of the operation example).

  FIG. 38 is a diagram for explaining the operation of the image database by the user. Here, the operation of the image database 2 of FIG. 35 by the user will be described. As shown in FIG. 38, a user who has been authenticated may make a request for adding an image, adding or changing tag information to the DBMS 21 using SQL or the like without using the authentication system 1. it can. At the time of image search, the elements of the image data shown in FIG. 36 can be used. When the operation on the image database 2 is completed, the DBMS 21 returns the operation result (whether there is an error, the search result, etc.) to the user.

  FIG. 39 is a diagram for explaining an operation when a service using an image database is implemented as a WEB application. Here, an authentication system 42 and an interface 43 for operating the database 22 using SQL by the user are implemented as a WEB application 41.

  Communication between the user and the WEB service 3 is performed via HTTP or HTTPS. The user first accesses the authentication start page, and requests authentication to the WEB server 4 by the GET method. Then, the WEB application 41 requests the DBMS 21 for an image belonging to the image group 1 and an image belonging to the image group 2 to the DBMS 21 through a language for requesting the database 22 such as SQL from the authentication system 42. The DBMS 21 selects one image ID randomly from the image IDs belonging to the image group 1 using the image classification data in FIG. 37, and randomly selects one image ID from the image IDs belonging to the image group 2. The image IDs are selected, images corresponding to all the selected IDs are searched and extracted from the image data, and the result is returned to the authentication system 42 together with the tag information.

  Then, the WEB application 41 displays an authentication image presentation screen as shown in FIG. 40 on the user's WEB browser. On the screen shown in FIG. 40, tag information that is more appropriate for the user who has observed the authentication image portions 101 and 102 is entered in the answer columns 103 and 104. Further, when the transmission button 105 is pressed, the response contents (test results) in the response fields 103 and 104 are transmitted to the WEB server 4 by the HTTP POST method or the like. In the WEB server 4, authentication is performed by comparing the response content in the response field 103 in the received response content with the tag information assigned in advance to the images belonging to the image group 1 on the database 22. Specifically, the correct answer rate is calculated by calculating the correct answer rate indicating how many pieces of tag information previously given to the authentication image presented in the authentication image unit 101 are included in the transmitted answer. When the rate is equal to or higher than a predetermined threshold (for example, 40% to 50%), authentication is performed to determine that the user is a human.

  When it is determined that the user is a human, the authentication system displays a screen as shown in FIG. 41 on the user's web browser (strictly, the web browser that operates on the information processing device used by the user), and the user Enter the user name and password and press the send button. These are transmitted to the WEB server 4 by the POST method, and when the user name and password are those of the authorized user, the WEB server 4 displays a screen for prompting image search or image posting as shown in FIG. Prompt user selection. The user clicks one of them, and transmits a request for image search or image posting to the WEB server 4 side by the POST method. When the user selects image search, the WEB server 4 displays a screen for prompting input related to image search as shown in FIG. 43 on the user's WEB browser. The user enters a search word in the column of the item to be searched, and checks a check box that indicates the display order, and then presses the send button. Then, this request is transmitted to the WEB server 4 by the POST method, and the DB operation interface 43 transmits this request to the DBMS 21 by SQL. The DBMS 21 searches the database 22 for image data that matches the request, and returns the resulting image and its tag information to the DB operation interface 43 in the indicated display order. These are transmitted from the WEB server 4 to the user, and as a result, an image search result screen as shown in FIG. 44 is displayed on the user's WEB browser. Here, the display order of the search results is displayed in the display order indicated in FIG. In the third embodiment, when tag information is selected as a search term, the display order can be configured to be displayed in ascending order or descending order as instructed according to the response rate of the tag. When the user selects “image posting” on the screen of FIG. 43, a screen for prompting input related to the image posting as shown in FIG. 45 is displayed on the user's WEB browser. Here, the user selects an image file, enters tag information for the image, and presses a send button. These are sent to the DB operation interface 43 via the POST method, and the DB operation interface 43 transmits SQL for adding data to the DBMS 21.

  By adopting such a configuration, tag information is automatically attached to the image database 2 and the web service 3 using the image database 2 even when an image to which tag information is not attached is used. Whether or not the user is a human being with high accuracy without preparing a large amount of image data with tag information separately because appropriate tag information is selected from tag information attached by a large number of users. Can be determined, and the accuracy of the search can be improved.

  In this way, it is determined whether or not the user is a human being, and only the user who is determined to be a human is allowed to add an image and edit data, and the image database 2 is used. Web service 3 can be provided.

  By having such a feature, it is possible to determine whether or not the user is a human with high accuracy without preparing a large amount of separate data in the image database and the service using the image database. In addition, the accuracy of the search can be improved.

  In addition, when using tag information associated with an image as a search term in image search, the display order of search results is changed using an answer rate, and the image database 2 WEB service 3 using can be provided.

  By having such a feature, it is possible to determine whether or not the user is a human with high accuracy without preparing a large amount of separate data in the image database and the image sharing service, and to improve the search accuracy. It becomes possible to improve.

  The advantages of the authentication system according to the third embodiment that has been described above will be supplemented below. The description will be made in comparison with the prior art.

  In a conventional system using content recognition of photographic images, the more frequently the same photo is used, the easier it is to estimate the relationship between the image and its assigned word. This requires a large amount of images that are preliminarily given words representing the object names included in the images and the scenes that the images mean. Since it is very difficult to obtain such an image database, actual operation of a visual anti-robot test system using photographic images has become very difficult.

  However, the authentication system according to the third embodiment can facilitate the construction of an image database required in such a system.

  In recent years, there have been image sharing services on the web and stock photo services that allow users to post images, share them with other users, and use them for their own programs and documents for free or for free. It is gaining popularity. In these services, an object name included in each image and a word representing a scene represented by the image are given in advance as tag information by a poster, and an image search can be performed using this tag information. However, on such a WEB service, since the tag given in advance depends on the subjectivity of the grantor, it is very difficult for the searcher to search for a desired photo from a vast number of images.

  However, according to the authentication system according to the third embodiment, the quality of such tag information can be improved and the search accuracy can be improved.

  As described above, the present invention has been described based on each embodiment, but the present invention is not limited to the requirements shown here, such as combinations with other elements listed in the above embodiments. With respect to these points, the present invention can be changed within a range that does not detract from the gist of the present invention, and can be appropriately determined according to the application form.

It is a figure which shows the structural example of the authentication system which concerns on Embodiment 1. FIG. It is a figure which shows the function structural example of the authentication system which concerns on Embodiment 1. FIG. 3 is a flowchart illustrating an operation example of the authentication system according to the first embodiment. 6 is a flowchart illustrating another operation example of the authentication system according to the first embodiment. It is an example of the image for authentication used in the conventional authentication system. 4 is a first example of an authentication image according to the first embodiment. FIG. 6 is a diagram for supplementarily explaining a first example of an authentication image according to the first embodiment. 6 is a second example of an authentication image according to the first embodiment. It is an example of the moving image for authentication which concerns on Embodiment 1. FIG. FIG. 10 is a diagram (part 1) for supplementary explanation of FIG. 9; FIG. 10 is a diagram (part 2) for supplementary explanation of FIG. 9; 6 is a third example of an authentication image according to the first embodiment. It is a figure for supplementary explanation of FIG. 6 is a fourth example of an authentication image according to the first embodiment. FIG. 15 is a diagram for supplementarily explaining FIG. 14. 10 is a fifth example of an authentication image according to the first embodiment. 10 is a sixth example of an authentication image according to the first embodiment. 10 is a seventh example of an authentication image according to the first embodiment. 10 is an eighth example of an authentication image according to the first embodiment. 10 is a ninth example of an authentication image according to the first embodiment. 10 is a tenth example of an authentication image according to the first embodiment. 6 is a first example of an authentication moving image presentation screen according to the second embodiment. 6 is a first example of an authentication moving image according to the second embodiment. FIG. 24 is a diagram for supplementary explanation of FIG. 23. It is a 2nd example of the moving image for authentication which concerns on Embodiment 2. FIG. It is a 2nd example of the presentation screen of the moving image for authentication which concerns on Embodiment 2. FIG. It is a 3rd example of the moving image for authentication which concerns on Embodiment 2. FIG. It is a 4th example of the moving image for authentication which concerns on Embodiment 2. FIG. It is an example of the presentation screen of the moving image for authentication which concerns on Embodiment 2. FIG. 10 is a flowchart illustrating an example of the operation of the authentication system according to the third embodiment. 10 is a flowchart illustrating another operation example of the authentication system according to the third exemplary embodiment. 12 is a flowchart illustrating a first modification of the operation of the authentication system according to the third embodiment. 10 is a flowchart illustrating a second modification of the operation of the authentication system according to the third embodiment. 10 is a flowchart illustrating a third modification of the operation of the authentication system according to the third embodiment. It is a figure which shows the system configuration example of the authentication system which concerns on Embodiment 3. FIG. It is an example of the data structure of the image for authentication. It is an example of the data structure which classifies the image for authentication. It is a figure for demonstrating operation of the image database by a user. It is a figure for demonstrating operation when the service using an image database is mounted as a WEB application. It is an example of the presentation screen of the image for authentication which a WEB application presents. It is a display example of a screen that prompts input of a user name and a password. It is a display example of a screen that prompts input of an image search or an image posting. It is a display example of a screen that prompts input related to an image search. It is an example of a display of a screen of an image search result. It is a display example of a screen that prompts input related to image posting.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Authentication system 10 Client apparatus 20 Server apparatus 110 Input part 120 Display part 130 Communication part 140 Control part 210 Authentication part 220 Authentication image generation part 230 Authentication image presentation part 240 Communication part 250 Service provision part 260 Control part

Claims (17)

An authentication method in an authentication device for authenticating a user,
An authentication image in which an image corresponding to a character and / or symbol is provided on a background, and there is no authentication due to an image density difference between the background and the image corresponding to the character and / or symbol An image generation process for authentication to generate an image for use;
An authentication image presentation step of presenting the authentication image generated in the authentication image generation step to the user;
An authentication step for performing authentication by comparing character and / or symbol information input by a user based on the authentication image presented in the authentication image presenting step with characters and / or symbols in the authentication image; ,
An authentication method characterized by comprising:   The authentication image generated in the authentication image generation step is different from the first texture on the background made of the first texture, and forms a second image that corresponds to the character and / or symbol. The authentication method according to claim 1, wherein the authentication information is an image provided with authentication information.   The authentication method according to claim 2, wherein average values of image densities of the first texture and the second texture are substantially equal.   2. The authentication method according to claim 1, wherein the authentication image generated in the authentication image generation step is a stereogram image in which an image corresponding to the character and / or symbol is embedded.   2. The authentication according to claim 1, wherein the authentication image generated in the authentication image generation step is an image in which each of the characters and / or symbols is composed of a plurality of characters and / or symbols. Method.   The authentication method according to claim 1, wherein the authentication image generated in the authentication image generation step is an image composed of a point group indicating characteristics of the character and / or symbol. In the authentication image presentation step, the user is further prompted to select characters and / or symbols included in the authentication image,
In the authentication step, authentication is performed by comparing the character and / or symbol information selected by the user based on the authentication image presented in the authentication image presentation step with the character and / or symbol in the authentication image. The authentication method according to claim 1, wherein the authentication method is performed. In the authentication image presentation step, the user is further prompted to select one or more conditions satisfying a predetermined condition among the plurality of authentication images and the plurality of authentication images,
2. The authentication is performed by comparing an authentication image selected by a user based on the authentication image presented in the authentication image presenting step with the predetermined condition. The authentication method as described in any one of thru | or 6. An authentication method in an authentication device for authenticating a user,
Authentication information comprising a second texture for forming an image corresponding to a character and / or symbol is provided on a background comprising the first texture, and the positional relationship between the background and the authentication information is hourly. An authentication video generation process for generating an authentication video that changes to
A video presentation process for authentication that presents to the user the video for authentication generated in the video generation process for authentication;
An authentication step for performing authentication by comparing character and / or symbol information input by a user based on the authentication moving image presented in the authentication moving image presentation step and the characters and / or symbols in the authentication moving image; ,
An authentication method characterized by comprising:   The authentication method according to claim 9, wherein the authentication moving image generated in the authentication moving image generation step is a continuation of an image composed of a point group indicating characteristics of the characters and / or symbols. In the authentication video presentation step, the user is further prompted to select characters and / or symbols included in the authentication video,
In the authentication step, authentication is performed by comparing the character and / or symbol information selected by the user based on the authentication moving image presented in the authentication moving image presentation step with the characters and / or symbols in the authentication moving image. The authentication method according to claim 9 or 10, wherein: In the authentication video presentation step, the user is further prompted to select one or more conditions satisfying a predetermined condition among the plurality of authentication videos and the plurality of authentication videos,
The authentication step includes performing authentication by comparing an authentication moving image selected by a user based on the authentication moving image presented in the authentication moving image presentation step with the predetermined condition. The authentication method according to 9 or 10. An authentication device for authenticating a user,
An authentication image in which an image corresponding to a character and / or symbol is provided on a background, and there is no authentication due to an image density difference between the background and the image corresponding to the character and / or symbol Authentication image generating means for generating an image,
Authentication image presenting means for presenting an authentication image generated by the authentication image generating means to a user;
Authentication means for performing authentication by comparing character and / or symbol information input by a user based on the authentication image presented by the authentication image presenting means with the characters and / or symbols in the authentication image; ,
An authentication apparatus comprising: An authentication device for authenticating a user,
Generating an authentication image provided with authentication information comprising a second texture that forms an image corresponding to a character and / or a symbol on a background comprising the first texture and different from the first texture; Authentication image generating means;
Authentication image presenting means for presenting an authentication image generated by the authentication image generating means to a user;
Authentication means for performing authentication by comparing character and / or symbol information input by a user based on the authentication image presented by the authentication image presenting means with the characters and / or symbols in the authentication image; ,
An authentication apparatus comprising: An authentication device for authenticating a user,
Authentication image generation means for generating a stereogram image in which an image corresponding to characters and / or symbols is embedded as an authentication image;
An authentication image presentation step of presenting an authentication image generated by the authentication image generation means to a user;
Authentication means for performing authentication by comparing character and / or symbol information input by a user based on the authentication image presented by the authentication image presenting means with the characters and / or symbols in the authentication image; ,
An authentication apparatus comprising: An authentication device for authenticating a user,
Authentication information comprising a second texture for forming an image corresponding to a character and / or symbol is provided on a background comprising the first texture, and the positional relationship between the background and the authentication information is hourly. An authentication video generation means for generating an authentication video that changes to
Authentication video presentation means for presenting to the user the authentication video generated by the authentication video generation means;
Authentication means for performing authentication by comparing character and / or symbol information input by a user based on the authentication video presented by the authentication video presentation means and characters and / or symbols in the authentication video; ,
An authentication apparatus comprising: An authentication device for authenticating a user,
Authentication image generating means for generating an image corresponding to a character and / or a symbol, each of the character and / or symbol being composed of a plurality of characters and / or symbols, as an authentication image;
Authentication image presenting means for presenting an authentication image generated by the authentication image generating means to a user;
Authentication means for performing authentication by comparing character and / or symbol information input by a user based on the authentication image presented by the authentication image presenting means with the characters and / or symbols in the authentication image; ,
An authentication apparatus comprising: