CN114025350B - Dual authentication method based on password and frequency offset - Google Patents

Abstract

The invention provides a dual authentication method based on password and frequency offset, which includes: step 1, the device to be authenticated sends a probe request frame signal with a specific SSID to a general software radio peripheral, and the general software radio peripheral is connected to the host; Step 2: Run GNU radio to perform signal processing on the received signal according to the signal received by the general software radio peripheral, and obtain the carrier frequency offset characteristics of the device to be authenticated; Step 3: Use the nearest neighbor pattern matching algorithm to obtain the carrier frequency offset characteristics of the device to be authenticated. Similarity calculation is performed between the carrier frequency offset characteristics and the stored carrier frequency offset characteristics of all authorized users. The present invention extracts the frequency offset fingerprint characteristics of wireless smart devices through universal software radio peripherals, and uses the frequency offset to identify the smart devices. By passing the password and frequency offset dual authentication mode, the wireless network identification mechanism is enhanced and illegal devices are avoided. access, network security is improved.

Description

Two-factor authentication method based on password and frequency offset

Technical field

The invention relates to the field of security technology, and in particular to a dual authentication method based on password and frequency offset.

Background technique

Wireless LAN is now everywhere and has become a necessary part of everyone's life. Through wireless networks, everyone can conduct a series of important activities such as network communication and work communication. However, the popularity of wireless LAN has also made its security issues the focus of attention. The borderless and open signals of wireless networks not only bring great convenience to users, but also expose wireless LANs to more security threats. Therefore, effective wireless security solutions are needed to ensure the safe access and management of wireless LANs. The identity authentication mechanism for wireless LAN access mainly includes key-based authentication and identification based on access device MAC address, IP address and other information. However, this information can easily be sniffed, disguised and tampered by illegal intruders, thus damaging the wireless network. Conduct eavesdropping. In addition, wireless network security protocols generally have some flaws. Illegal intruders can steal the key through certain means, and thus can invade the wireless network and hijack information. In October 2017, MathyVanhoef announced a key reinstallation attack against the WAP2 protocol, which allowed the attacker to read all traffic on the target wireless network connection. Therefore, it is crucial and urgent to develop an authentication system that can prevent network attacks and enhance wireless network security.

Due to manufacturing tolerances of electronic components and the degradation and aging effects of components, even wireless devices of the same model and batch have differences in actual hardware parameters, and this hardware difference will be reflected in communication signals. Today, with the increasing development of science and technology, more and more researchers at home and abroad are studying radio frequency fingerprint extraction and identification methods for wireless communication equipment. Just as everyone has their own unique fingerprint, every wireless device also has its own unique fingerprint "RF fingerprint." Extracting and identifying fingerprint features of wireless smart devices at the physical layer, and then using hardware individual authentication methods to implement wireless device access control, can assist and enhance the traditional wireless network identification mechanism, thus providing a greater security for wireless networks. protection.

Contents of the invention

The present invention provides a dual authentication method based on password and frequency offset. Its purpose is to solve the problem that the information of the access device is easily sniffed, disguised and tampered by illegal intruders, and the wireless network is easily eavesdropped and the information is processed by illegal intruders. Hijacking issue.

In order to achieve the above objectives, embodiments of the present invention provide a dual authentication method based on password and frequency offset, including:

Step 1: The device to be authenticated sends the probe request frame signal with a specific SSID to the general software radio peripheral, and the general software radio peripheral is connected to the host;

Step 2: Run GNU radio based on the signal received by the general software radio peripheral to perform signal processing on the received signal to obtain the carrier frequency offset characteristics of the device to be certified;

Step 3: Calculate the similarity between the carrier frequency offset characteristics of the device to be authenticated and the stored carrier frequency offset characteristics of all authorized users through the nearest neighbor pattern matching algorithm;

Step 4: Determine whether to allow the device to be authenticated to access the wireless network based on the similarity between the calculated carrier frequency offset characteristics of the device to be authenticated and the stored carrier frequency offset characteristics of all authorized users and the correctness of the password verification of the device to be authenticated.

Among them, the step 2 specifically includes:

Step 21: Perform conjugate correlation on each probe request frame signal in the received signal, obtain the autocorrelation coefficient corresponding to each probe request frame signal, and determine whether the autocorrelation coefficient corresponding to each probe request frame signal is higher than the Once the threshold is set, when the autocorrelation coefficient corresponding to the current probe request frame signal is higher than the first set threshold, step 22 is executed. When the autocorrelation coefficient corresponding to the current probe request frame signal is lower than the first set threshold, the The current probe request frame signal is filtered out.

Among them, the step 21 specifically includes:

Calculate the autocorrelation coefficient as follows:

Among them, a[n] represents the autocorrelation function value, k represents the value in the adjustable window, s[n] represents the frame signal sequence, n represents the number of the frame sequence symbol, represents the complex conjugate of s, p[n] represents the average power, N _win represents the adjustable window, and c[n] represents the autocorrelation coefficient.

Wherein, the step 2 also includes:

Perform the following steps for each probe request frame signal filtered out in step 21:

Step 22: Perform frame synchronization on the probe request frame signal through the time domain delay correlation algorithm of the short training sequence, and perform coarse carrier frequency offset estimation. The steps are as follows:

Delay correlation is performed through the first 5 symbol segments of the short training sequence to estimate the coarse carrier frequency offset, as follows:

in, represents the estimated coarse carrier frequency offset, S _m represents the symbols of the first 5 symbol segments of the short training sequence, m represents the number of the symbols of the first 5 symbol segments of the short training sequence, m=0,1,...,79; arg () represents the phase operator,/> Represents the conjugate of the 16th symbol after S _m ;

By estimated coarse carrier frequency offset Compensate for long training sequence symbols as follows:

Among them, S _n represents the long training sequence symbol, n represents the number of the long training sequence symbol, n = 0, 1, ..., 127, and S' _n represents the long training sequence symbol after the estimated coarse carrier frequency offset compensation.

Wherein, the step 2 also includes:

Step 23: Perform fine carrier frequency offset estimation based on the estimated coarse carrier frequency offset compensated long training sequence symbols, as follows:

in, Represents the estimated precise carrier frequency offset,/> Represents the conjugate of the 64th symbol after S _n '.

Wherein, the step 2 also includes:

Step 24: Add the estimated coarse carrier frequency offset and the estimated fine carrier frequency offset to obtain the estimated total carrier frequency offset.

Step 25: Obtain carrier frequency offset characteristics based on the estimated total carrier frequency offset As follows:

Among them, BW is the channel bandwidth.

Wherein, the step 2 also includes:

Step 26: Equalize the signal based on the frequency domain estimated channel, including the following steps;

Step 261: Compensate the probe request frame signal according to the corresponding carrier frequency offset characteristics;

Step 262: Perform FFT transformation on the probe request frame signal after frequency offset compensation, and convert the probe request frame signal from the time domain to the frequency domain;

Step 263: Pass the converted probe request frame signal through the WiFi frame equalizer to check the value on the pilot carrier according to the transmitted pilot symbol, and estimate the constellation diagram of the carrier symbol by subtracting the remaining frequency offset;

Step 27: Perform pilot removal and cyclic prefix on the probe request frame signal according to the estimated constellation diagram of the carrier symbol, and perform deinterleaving, Viterbi decoding and descrambling on the probe request frame signal after the cyclic prefix to obtain the probe request frame. According to the load information of the signal, the SSID identifier of the probe request frame signal is extracted based on the load information, and the carrier frequency offset is used as the fingerprint of the probe request frame signal.

Among them, the step 3 specifically includes:

Express the density of the sample set of authorized devices as:

Among them, D _k1 represents the authorized device sample set, k = A, B, C, D, E, F, d _ij represents the distance between sample i and sample j, and N _k represents the number of samples in the authorized device sample set. ,k=A,B,C,D,E,F.

Among them, the step 3 also includes:

Add the device sample set to be authenticated to each authorized device sample set. The density of multiple new sample sets is:

Among them, N _h represents the number of samples in the sample set of the device to be authenticated, N _h +1 represents the index of the device sample to be authenticated, when D _k1 ＞= D _k2 + th, the sample set is considered unauthorized, and th represents Second set threshold.

Among them, the step 4 specifically includes:

Step 41, find the minimum value of the density difference between the original sample set and the new sample set:

ch _k ＝D _k1 -D _k2 , k＝A,B,C,D,E,F (10)

ch＝min(ch _k ) (11)

Among them, ch represents the highest similarity of carrier frequency offset;

Step 42: Determine whether the highest similarity ch of the carrier frequency offset of the device to be authenticated is higher than the second set threshold th;

Step 43: When the highest similarity ch of the carrier frequency offset of the device to be authenticated is higher than the second set threshold th, execute step 43; when the highest similarity ch of the carrier frequency offset of the device to be authenticated is not higher than the second set threshold At th time, the device to be authenticated is an unauthorized device, and the device to be authenticated is not allowed to access the wireless network, ending;

Step 44: Determine whether the password of the device to be authenticated is correct;

Step 45: When the password of the device to be authenticated is correct, perform step 45; when the password of the device to be authenticated is incorrect, the device to be authenticated is an unauthorized device and the device is not allowed to access the wireless network, ending;

Step 46: The device to be authenticated is an authorized device and is allowed to access the wireless network.

The above solution of the present invention has the following beneficial effects:

The dual authentication method based on password and frequency offset described in the above embodiments of the present invention extracts the frequency offset fingerprint characteristics of wireless smart devices through low-cost customized universal software radio peripherals, and uses the frequency offset to identify the smart devices , during authentication, only if the two authentication processes of password authentication and frequency offset authentication are passed at the same time, the authentication will be judged as passed. Through this double authentication mode, the wireless network identification mechanism is enhanced and the security of the network is improved.

Description of drawings

Figure 1 is a flow chart of the password and frequency offset dual authentication of the present invention;

Figure 2 is a flow chart for extracting carrier frequency offset features of equipment to be authenticated according to the present invention;

Figure 3 is a frequency offset distribution histogram of different equipment to be authenticated according to the present invention;

Figure 4 shows the authentication accuracy rate of each device to be authenticated according to the present invention.

Detailed ways

In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

The present invention aims at the problem that the information of the existing access equipment is easily sniffed, disguised and tampered by illegal intruders, and the wireless network is easily eavesdropped and information hijacked by illegal intruders. It provides a dual-password based on password and frequency offset. Authentication method.

As shown in Figures 1 to 4, the embodiment of the present invention provides a dual authentication method based on password and frequency offset, including: Step 1, the device to be authenticated sends a probe request frame signal with a specific SSID to a general software radio Peripheral, the general software radio peripheral is connected to the host; step 2, run GNU radio according to the signal received by the general software radio peripheral to perform signal processing on the received signal, and obtain the carrier frequency offset characteristics of the device to be certified; step 3, The nearest neighbor pattern matching algorithm is used to calculate the similarity between the carrier frequency offset characteristics of the device to be authenticated and the stored carrier frequency offset characteristics of all authorized users; step 4, based on the calculated carrier frequency offset characteristics of the device to be authenticated and the ones that have been stored The similarity of the stored carrier frequency offset characteristics of all authorized users and the correctness of the password verification of the device to be authenticated are used to determine whether the device to be authenticated is allowed to access the wireless network.

The dual authentication method based on password and frequency offset described in the above embodiments of the present invention includes password authentication and frequency offset authentication. Through the password and frequency offset dual authentication mode, the access of illegal devices can be avoided and the security of the wireless network can be improved. Specifically, turn on the WiFi switch of the smart device, add other networks, enter the corresponding information in the network name and password, so that the device to be authenticated transmits a probe request frame signal with a specific SSID, and uses the general software radio peripheral B210 as the signal receiving device. Connect the host, run GUN radio to process the signal, then extract the carrier frequency offset of the proberequest frame signal of a specific SSID, and determine whether the highest similarity between the carrier frequency offset of the device to be authenticated and the stored authorized device carrier frequency offset is higher than the second setting Set a threshold. If the highest similarity is higher than the second set threshold, determine whether the password is correct. When the password is correct, the device to be authenticated is an authorized device and is allowed to access the wireless network. Otherwise, it is an unauthorized device and is refused access to the wireless network. . If the highest similarity is lower than the second set threshold, the device to be authenticated is directly determined to be an unauthorized device and access to the wireless network is refused. In this double verification mode, the security of the wireless network can be further improved.

The dual authentication method based on password and frequency offset described in the above embodiment of the present invention makes full use of commonly used smartphones, turns on the COTS smartphone WiFi switch and causes it to transmit a probe request frame signal with a specific SSID, which is transmitted over the air. , the general software radio peripheral receives the probe request frame signal, but in addition to receiving the probe request frame sent by the experimental smartphone, the general software radio peripheral also receives other signals from other devices. Therefore, in order to reduce the influence of other signals, the center frequency of the experimental platform is set to 5.17GHz, the sampling rate is 20MSa/s, and the channel bandwidth BW is 20MHz. There are fewer signals from other devices in this channel.

Among them, the step 2 specifically includes: step 21, perform conjugate correlation on each probe request frame signal in the received signal, obtain the autocorrelation coefficient corresponding to each probe request frame signal, and determine each probe request frame signal Whether the corresponding autocorrelation coefficient is higher than the first set threshold. When the autocorrelation coefficient corresponding to the current probe request frame signal is higher than the first set threshold, perform step 22. When the autocorrelation coefficient corresponding to the current probe request frame signal is low At the first set threshold, the current probe request frame signal is filtered out.

Among them, the step 21 specifically includes: calculating the autocorrelation coefficient, as shown below:

Among them, a[n] represents the autocorrelation function value, k represents the value in the adjustable window, s[n] represents the frame signal sequence, n represents the number of the frame sequence symbol, represents the complex conjugate of s, p[n] represents the average power, N _win represents the adjustable window, and c[n] represents the autocorrelation coefficient.

Wherein, step 2 also includes: performing the following steps for each probe request frame signal filtered out in step 21:

Step 22: Perform frame synchronization on the probe request frame signal through the time domain delay correlation algorithm of the short training sequence, and perform coarse carrier frequency offset estimation. The steps are as follows:

Delay correlation is performed through the first 5 symbol segments of the short training sequence to estimate the coarse carrier frequency offset, as follows:

in, represents the estimated coarse carrier frequency offset, S _m represents the symbols of the first 5 symbol segments of the short training sequence, m represents the number of the symbols of the first 5 symbol segments of the short training sequence, m=0,1,...,79; arg () represents the phase operator,/> Represents the conjugate of the 16th symbol after S _m ;

By estimated coarse carrier frequency offset Compensate for long training sequence symbols as follows:

Among them, S _n represents the long training sequence symbol, n represents the number of the long training sequence symbol, n = 0, 1, ..., 127, and S' _n represents the long training sequence symbol after the estimated coarse carrier frequency offset compensation.

Wherein, the step 2 also includes: step 23, performing fine carrier frequency offset estimation based on the estimated coarse carrier frequency offset compensated long training sequence symbols, as follows:

in, Represents the estimated precise carrier frequency offset,/> Represents the conjugate of the 64th symbol after S _n '.

Wherein, the step 2 also includes: step 24, adding the estimated coarse carrier frequency offset and the estimated fine carrier frequency offset to obtain the estimated total carrier frequency offset.

Step 25: Obtain carrier frequency offset characteristics based on the estimated total carrier frequency offset As follows:

Among them, BW is the channel bandwidth.

In the dual authentication method based on password and frequency offset described in the above embodiments of the present invention, the steps for extracting carrier frequency offset features of the device to be authenticated are as follows: 1. Conjugate the received signal, and when the correlation peak is obtained, it is considered that the smart device has received the transmission IEEE802.11a/g signal for subsequent processing; 2. Use the time domain delay correlation algorithm of the short training sequence to synchronize the frame and roughly estimate the carrier frequency offset. 3. Use the long training sequence to cross-correlate with the received signal to synchronize the symbols and accurately estimate the carrier frequency offset/> Obtain the final carrier frequency offset estimate through the second and third steps/> Then get the carrier frequency offset/> 4. Estimate the channel in the frequency domain and perform equalization; 5. Remove the pilot and cyclic prefix, deinterleave, Viterbi decoding, and descrambling to obtain the frame signal load information, and extract the SSID of the probe request frame signal from the load information The identifier uses the carrier frequency offset as the fingerprint of the probe request frame signal.

In the dual authentication method based on password and frequency offset described in the above embodiments of the present invention, when c[n] is higher than the first set threshold, it indicates that the IEEE 802.11a/g signal has been received, and subsequent processing is performed; IEEE802.11a /g is a typical burst packet type wireless LAN. According to the time domain correlation characteristics of its preamble training sequence, using the data-assisted frequency offset estimation algorithm, the synchronization and frequency offset estimation of the received signal can be completed within a single training symbol, and then Then compensate for valid information. In order to make the frequency offset estimate more accurate, the carrier frequency offset is normally estimated to a smaller range first, and then the remaining frequency offset is further estimated. That is, the short training sequence is used for coarse frequency offset estimation and compensation, and the long training sequence is used for fine frequency offset estimation. The total frequency offset estimate is equal to the coarse frequency offset estimate plus the fine frequency offset estimate. According to formula (7), the receiver can finally be obtained. frequency deviation of the signal.

Among them, the step 2 also includes: step 26, equalizing the signal based on the frequency domain estimated channel, including the following steps; step 261, compensating the probe request frame signal according to the corresponding carrier frequency offset characteristics; step 262, adjusting the frequency offset The compensated probe request frame signal undergoes FFT transformation to convert the probe request frame signal from the time domain to the frequency domain; step 263, pass the converted probe request frame signal through the WiFi frame equalizer to check the pilot carrier according to the transmitted pilot symbol Value of The signal is deinterleaved, Viterbi decoded and descrambled to obtain the load information of the probe request frame signal. The SSID identifier of the probe request frame signal is extracted based on the load information, and the carrier frequency offset is used as the fingerprint of the probe request frame signal.

The dual authentication method based on password and frequency offset described in the above embodiment of the present invention removes 4 pilots and cyclic prefixes, leaving 48 data carriers carrying actual information, and deinterleaves 48 carrier symbols. Viterbi decoding, descrambling, and finally obtaining the frame signal load information, extracting the SSID identifier of the frame signal from the load information, using the carrier frequency offset as the fingerprint of the frame signal, and using the frequency offset fingerprint feature to identify each smart device sort.

Among them, the step 3 specifically includes: expressing the density of the authorized device sample set as:

Among them, D _k1 represents the authorized device sample set, k = A, B, C, D, E, F, d _ij represents the distance between sample i and sample j, and N _k represents the number of samples in the authorized device sample set. ,k=A,B,C,D,E,F.

Wherein, the step 3 also includes: adding the device sample set to be authenticated to each authorized device sample set respectively. The density of the multiple new sample sets is:

Among them, N _h represents the number of samples in the sample set of the device to be authenticated, N _h +1 represents the index of the device sample to be authenticated, when D _k1 ＞= D _k2 + th, the sample set is considered unauthorized, and th represents Second set threshold.

In the dual authentication method based on password and frequency offset described in the above embodiment of the present invention, there are 6 authorized devices stored by default, and their carrier frequency offset fingerprint feature sets are A, B, C, D, E, and F respectively. . The densities of their carrier frequency offset fingerprint feature sets are D _A1 , D _B1 , D _C1 , D _D1 , D _E1 , and D _F1 respectively. Add the carrier frequency offset fingerprint feature samples of the device to be authenticated to the carrier frequency offset fingerprint feature sets of the existing 6 authorized devices. The densities of the new sample sets are D _A2 , D _B2 , D _C2 , D _D2 , and D _E2 respectively. ,D _F2 .

Among them, the step 4 specifically includes: step 41, finding the minimum value of the density difference between the original sample set and the new sample set:

ch _k ＝D _k1 -D _k2 , k＝A,B,C,D,E,F (10)

ch＝min(ch _k ) (11)

Among them, ch represents the highest similarity of carrier frequency offset;

Step 42: Determine whether the highest similarity ch of the carrier frequency offset of the device to be authenticated is higher than the second set threshold th;

Step 43: When the highest similarity ch of the carrier frequency offset of the device to be authenticated is higher than the second set threshold th, execute step 43; when the highest similarity ch of the carrier frequency offset of the device to be authenticated is not higher than the second set threshold At th time, the device to be authenticated is an unauthorized device, and the device to be authenticated is not allowed to access the wireless network, ending;

Step 44: Determine whether the password of the device to be authenticated is correct;

Step 45: When the password of the device to be authenticated is correct, perform step 45; when the password of the device to be authenticated is incorrect, the device to be authenticated is an unauthorized device and the device is not allowed to access the wireless network, ending;

Step 46: The device to be authenticated is an authorized device and is allowed to access the wireless network.

The dual authentication method based on password and frequency offset described in the above embodiment of the present invention calculates the similarity between the carrier frequency offset characteristics of the device to be authenticated and the carrier frequency offset characteristics of all stored authorized devices. If the highest similarity obtained If the degree is greater than the second set threshold, it is determined that the device to be authenticated corresponding to the highest similarity is the authenticator that entered the carrier frequency offset characteristics; otherwise, the determination fails; after the authenticator is determined, it is determined whether the password is the correct password. If the password is correct, The authentication is successful, otherwise it is judged as failed.

The dual authentication method based on password and frequency offset described in the above embodiment of the present invention uses an ordinary commercial smart phone to verify the feasibility and stability of the dual authentication method based on password and frequency offset. The smart phone transmits a proberequest frame signal, The general software radio peripheral B210 is used as a signal receiving device. The general software radio peripheral is connected to the host through USB 3.0. The host runs GNU Radio for signal processing. The center frequency of the experimental platform is set to 5.17GHz, the sampling rate is 20MSa/s, and the channel bandwidth The BW is 20MHz. This channel has less interference signals. First, collect the carrier frequency offset fingerprint characteristics of 6 smartphones of different models or manufacturers in different scenarios and environments, store them in the system and set them as authorized devices, and then use these 6 smartphones respectively. Use one device to authenticate and access the wireless network, enter the correct password and the wrong password multiple times, record the accuracy of the experiment, use another 2 smart phone devices that have not been registered to store carrier frequency offset fingerprint characteristics, and enter the correct password multiple times to try Connect to the wireless network and record this experiment.

Verification results: Figure 3 shows the distribution histogram of the carrier frequency offset of 6 different devices. From the carrier frequency offset histograms of different devices, it can be seen that the range of the carrier frequency offset of most devices of different brands is different and they are all fixed. Within this range, the range of carrier frequency offset for smart devices of the same brand is the same, but the carrier frequency offset distribution histograms of six different devices are different. Therefore, the carrier frequency offset can be used to identify smart devices. Determine whether to allow access to the wireless network. Figure 4 shows the verification results of the dual authentication method based on password and frequency offset. It can be seen that for each device, the dual authentication method based on password and frequency offset can achieve an accuracy rate of more than 91%. Legal devices can be 100% allowed to access, and illegal devices can be intelligently detected and denied access.

The dual authentication method based on password and frequency offset described in the above embodiments of the present invention extracts the frequency offset fingerprint characteristics of wireless smart devices through low-cost customized universal software radio peripherals, and uses the frequency offset to identify the smart devices , during authentication, only when the two authentication processes of password authentication and frequency offset authentication are passed at the same time, the authentication will be judged as passed. Through this double authentication mode, the wireless network identification mechanism is enhanced, the security of the network is improved, and the access The information entering the device is not easily sniffed, disguised and tampered by illegal intruders.

The above is the preferred embodiment of the present invention. It should be pointed out that for those of ordinary skill in the art, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications can also be made. should be regarded as the protection scope of the present invention.

Claims (2)

1. A dual authentication method based on password and frequency offset, characterized by including: Step 1: The device to be authenticated sends the probe request frame signal with a specific SSID to the general software radio peripheral, and the general software radio peripheral is connected to the host; Step 2: Perform signal processing on the signal received by the general software radio peripheral to obtain the carrier frequency offset characteristics of the device to be certified; The step 2 specifically includes: Step 21: Perform conjugate correlation on each probe request frame signal in the received signal, obtain the autocorrelation coefficient corresponding to each probe request frame signal, and determine whether the autocorrelation coefficient corresponding to each probe request frame signal is higher than the Once the threshold is set, when the autocorrelation coefficient corresponding to the current probe request frame signal is higher than the first set threshold, step 22 is executed. When the autocorrelation coefficient corresponding to the current probe request frame signal is lower than the first set threshold, the The current probe request frame signal is filtered out; the step 21 specifically includes: Calculate the autocorrelation coefficient as follows: Among them, a[n] represents the autocorrelation function value, k represents the value in the adjustable window, s[n] represents the frame signal sequence, n represents the number of the frame sequence symbol, represents the complex conjugate of s, p[n] represents the average power, N _win represents the adjustable window, and c[n] represents the autocorrelation coefficient; Perform the following steps for each probe request frame signal filtered out in step 21: Step 22: Perform frame synchronization on the probe request frame signal through the time domain delay correlation algorithm of the short training sequence, and perform coarse carrier frequency offset estimation. The steps are as follows: Delay correlation is performed through the first 5 symbol segments of the short training sequence to estimate the coarse carrier frequency offset, as follows: in, represents the estimated coarse carrier frequency offset, S _m represents the symbols of the first 5 symbol segments of the short training sequence, m represents the number of the symbols of the first 5 symbol segments of the short training sequence, m=0,1,...,79; arg () represents the phase operator,/> Represents the conjugate of the 16th symbol after S _m ; By estimated coarse carrier frequency offset Compensate for long training sequence symbols as follows: Among them, S _n represents the long training sequence symbol, n represents the number of the long training sequence symbol, n=0,1,...,127, S' _n represents the long training sequence symbol after the estimated coarse carrier frequency offset compensation; Step 23: Perform fine carrier frequency offset estimation based on the estimated coarse carrier frequency offset compensated long training sequence symbols, as follows: in, Represents the estimated precise carrier frequency offset,/> Represents the conjugate of the 64th symbol after S′ _n ; Step 24: Add the estimated coarse carrier frequency offset and the estimated fine carrier frequency offset to obtain the estimated total carrier frequency offset. Step 25: Obtain carrier frequency offset characteristics based on the estimated total carrier frequency offset As follows: Among them, BW is the channel bandwidth; Step 26: Equalize the signal based on the frequency domain estimated channel, including the following steps; Step 261: Compensate the probe request frame signal according to the corresponding carrier frequency offset characteristics; Step 262: Perform FFT transformation on the probe request frame signal after frequency offset compensation, and convert the probe request frame signal from the time domain to the frequency domain; Step 263: Pass the converted probe request frame signal through the WiFi frame equalizer to check the value on the pilot carrier according to the transmitted pilot symbol, and estimate the constellation diagram of the carrier symbol by subtracting the remaining frequency offset; Step 27: Perform pilot removal and cyclic prefix on the probe request frame signal according to the estimated constellation diagram of the carrier symbol, and perform deinterleaving, Viterbi decoding and descrambling on the probe request frame signal after the cyclic prefix to obtain the probe request frame signal. The load information, extract the SSID identifier of the probe request frame signal based on the load information, and use the carrier frequency offset as the fingerprint of the probe request frame signal; Step 3: Calculate the similarity between the carrier frequency offset characteristics of the device to be authenticated and the stored carrier frequency offset characteristics of all authorized users through the nearest neighbor pattern matching algorithm; The step 3 specifically includes: Express the density of the sample set of authorized devices as: Among them, D _k1 represents the authorized device sample set, k = A, B, C, D, E, F, d _ij represents the distance between sample i and sample j, and N _k represents the number of samples in the authorized device sample set. ,k=A,B,C,D,E,F; Add the device sample set to be authenticated to each authorized device sample set. The density of multiple new sample sets is: Among them, N _h represents the number of samples in the sample set of the device to be authenticated, N _h +1 represents the index of the device sample to be authenticated, when D _k1 ＞= D _k2 + th, the sample set is considered unauthorized, and th represents second set threshold; Step 4: Determine whether to allow the device to be authenticated to access the wireless network based on the similarity between the calculated carrier frequency offset characteristics of the device to be authenticated and the stored carrier frequency offset characteristics of all authorized users and the correctness of the password verification of the device to be authenticated. 2. The dual authentication method based on password and frequency offset according to claim 1, characterized in that the step 4 specifically includes: Step 41, find the minimum value of the density difference between the original sample set and the new sample set: ch _k ＝D _k1 -D _k2 , k＝A,B,C,D,E,F (10) ch＝min(ch _k ) (11) Among them, ch represents the highest similarity of carrier frequency offset; Step 42: Determine whether the highest similarity ch of the carrier frequency offset of the device to be authenticated is higher than the second set threshold th; Step 43: When the highest similarity ch of the carrier frequency offset of the device to be authenticated is higher than the second set threshold th, execute step 43; when the highest similarity ch of the carrier frequency offset of the device to be authenticated is not higher than the second set threshold At th time, the device to be authenticated is an unauthorized device, and the device to be authenticated is not allowed to access the wireless network, ending; Step 44: Determine whether the password of the device to be authenticated is correct; Step 45: When the password of the device to be authenticated is correct, perform step 45; when the password of the device to be authenticated is incorrect, the device to be authenticated is an unauthorized device and the device is not allowed to access the wireless network, ending; Step 46: The device to be authenticated is an authorized device and is allowed to access the wireless network.