CN110008097B - Comprehensive evaluation method of service-oriented information system attack effectiveness - Google Patents

Abstract

A comprehensive evaluation method for attack efficiency of a service information system belongs to the technical field of network space security, and particularly relates to a comprehensive evaluation method for attack efficiency of a service information system. The invention provides a comprehensive evaluation method for attack efficiency of a four-dimensional weighted service information system. The invention comprises the following steps: 1) Establishing a multilevel evaluation index factor set of attack effectiveness of a service information system; 2) Establishing a weight set based on a four-dimensional weighting formula; 3) Establishing a multi-scale membership function of the terminal evaluation index factors; 4) And establishing a comprehensive evaluation model of attack efficiency of the service information system.

Description

Comprehensive evaluation method of service-oriented information system attack effectiveness

technical field

The invention belongs to the technical field of cyberspace security, and in particular relates to a method for comprehensively evaluating attack effectiveness of a service-oriented information system.

Background technique

Information system (Information system) is a human-computer integration system composed of computer hardware, network and communication equipment, computer software, information resources, information users and rules and regulations for the purpose of processing information flow. Information system has a general level model: physical layer, operating system layer, tool layer, data layer, functional layer, business layer and user layer. There are three structural modes of information systems: centralized structural mode, client/server (C/S) structural mode and browser/server (B/S) structural mode.

A service-oriented information system usually refers to an information system that adopts a service-oriented architecture (SOA, service-oriented architecture). Service-based information systems have basic characteristics such as reusability, loose coupling, well-defined interfaces, stateless service design and based on open standards. SOA is a component model that links different functional units of an application (called services) through well-defined interfaces and contracts between those services. The interface is defined in a neutral way, it should be independent of the hardware platform, operating system and programming language that implements the service. This allows services built into various such systems to interact in a unified and common way. SOA includes three roles: service requester, service provider and service registry. A service requester is an application, a software module, or another service that requires a service. The service requester initiates a query to the service in the registry, binds the service through transport, and executes the service function. The service requester executes the service according to the interface contract. A service provider is a network-addressable entity that accepts and executes requests from requesters. Service providers publish their services and interface contracts to the service registry so that service requesters can discover and access the service. A service registry is a service discovery enabler that contains a repository of available services and allows interested service requesters to look up service provider interfaces. Web service is a typical implementation of SOA technical specification. Web services are composed of three elements: Web Services Description Language (WSDL, Web Services Description Language), Unified Description, Definition and Integration (UDDI, Universal Description Definition and Integration) specification and Simple Object Access Protocol (SOAP, Simple Object Access Protocol). WSDL is used to describe services, UDDI is used to register and search services, and SOAP is used to transmit messages between service requesters and service providers.

The service-oriented information system takes service and sharing as the core, is based on open standards and protocols, and has the characteristics of loose coupling, support for efficient integration of application systems, and on-demand business processes. However, the system introduces more insecure factors while sharing and opening services, which increases the risk of being attacked. For example: because the system adopts a common runtime environment, data sharing and service call specifications between cross-platform heterogeneous systems, there are access array out-of-bounds, untrusted application escalation of privileges, memory allocation, assembly loading, exception handling, resource management and other security risks. For the process of system service subscription, query, release, etc., the attacker may cause the service resources of the service-oriented information system to Mutilation and information deception.

It is of great significance to comprehensively evaluate the attack effectiveness of service-oriented information systems in network attack and defense confrontation. By giving qualitative and quantitative evaluations on the effectiveness of attacks on service-oriented information systems, on the one hand, it will help the attackers to test the effectiveness of the attack behavior, and prompt them to continuously develop new attack techniques and methods; on the other hand, it will also help the defenders. Adopt more effective security strategies and methods to promote the improvement of its security performance.

Since the service-oriented information system is a complex information system, the attack on the service-oriented information system may cause various attack effects on the function and performance of the system and service, so the evaluation of the attack effectiveness of the service-oriented information system is a Comprehensive assessment questions. The so-called comprehensive evaluation is an evaluation method that uses mathematical methods to process and refine the information of multiple factors in a complex system to obtain its pros and cons. Comprehensive evaluation mainly includes two core technologies of weight determination and evaluation algorithm. At present, the weight determination methods mainly use Delphi (Delphi) method, Analytic Hierarchy Process (AHP, Analytic Hierarchy Process) method, variation coefficient method and mean square error method; evaluation algorithms generally include establishing factor sets, establishing weight sets, and establishing alternatives. Set, single factor evaluation, comprehensive evaluation and other basic steps.

The comprehensive evaluation of service-oriented information system attack effectiveness is a very complicated problem, mainly because the evaluation is generally a multi-objective evaluation; evaluation indicators include not only quantitative indicators, but also qualitative indicators that are difficult to quantify; human subjective influence. So far, although there are some publicly published reports, papers, patents and other materials on attack effectiveness evaluation methods for information systems and networks, there is no information on comprehensive evaluation methods for attack effectiveness of service-oriented information systems with four-dimensional empowerment.

Contents of the invention

The present invention aims at the above problems and provides a four-dimensional weighted service information system attack effectiveness comprehensive evaluation method.

To achieve the above object, the present invention adopts following technical scheme, and the present invention comprises the following steps:

1) Establish a multi-level evaluation index factor set for service-oriented information system attack effectiveness;

2) Establish a weight set based on the four-dimensional weighting formula;

3) Establish the multi-scale membership function of the terminal evaluation index factors;

4) Establish a comprehensive evaluation model of service information system attack effectiveness.

As a preferred solution, the step 2) weighting formula of the present invention is input by the index factor set weight vector calculated respectively by Delphi method, AHP method, variation coefficient method and mean square error method, through the first-level weighting preference factor α (0 ≤α≤1) and secondary weighting preference factor β(0≤β≤1) to comprehensively weight and calculate the weight set A,

A＝αβD _w +α(1-β)A _w +(1-α)(V _w +S _w ) (1)

In formula (1), D _w , A _w , V _w and S _w represent the index factor set weight vectors calculated by Delphi method, AHP method, variation coefficient method and mean square error method respectively; the first-level weighting preference factor α is greater than 0.5 indicates that the evaluation is biased towards subjective weighting; when α≠0, the secondary weighting preference factor β greater than 0.5 indicates that the Delphi method is more weighted in the Delphi method and the AHP method; the larger α and β indicate that the more subjective weighting is emphasized The smaller the α and β, the more emphasis on objective weighting; when α=0, formula (1) completely adopts objective weighting; when α=1, formula (1) completely adopts subjective weighting; when α= 1. When β=0, the formula (1) completely uses the AHP method for weighting; when α=1, β=1, the formula (1) completely uses the Delphi method for weighting.

As another preferred solution, step 1) of the present invention provides a service-based information system attack effectiveness multi-level evaluation index factor set as follows:

As another preferred solution, step 3 of the present invention) terminal evaluation index factor refers to the index factor represented by the terminal (leaf) node in the evaluation index factor set tree structure; the multi-scale membership function of the terminal evaluation index factor can be Divided into discrete scale membership functions and continuous scale membership functions, discrete scale membership functions are divided into binary discrete scale membership functions and multivariate discrete scale membership functions; the return value of the continuous scale membership function is any real number in the interval [0, 1]; two The return value of the meta-discrete-scale membership function is an integer of 0 or 1; the return value of the multi-variate discrete-scale membership function is a plurality (at least 3) of discrete real numbers in the interval [0, 1].

As another preferred solution, step 4) described in the present invention first establishes a single-factor evaluation model of service-oriented information system attack effectiveness; single-factor evaluation refers to evaluating from one factor alone, and adopts the terminal index factor membership function to calculate the pending The evaluated attack method j (j=1,2,…,n) respectively evaluates the i (i=1,2,…,m) index factor u _i ’s evaluation result vector

R _i =(r _i1 ,r _i2 ,…,r _in ),i=1,2,…,m (2)

Form each single factor evaluation result vector into a row matrix

Use the weight set of the four-dimensional weighting formula for each column of the single-factor evaluation matrix R

A＝(a ₁ ,a ₂ ,…,a _m ) (4)

Carry out a weighted average to obtain a comprehensive evaluation vector

Indicates the attack effectiveness evaluation results of n attack methods when m index factors are integrated;

In formula (4) and formula (5 ₎ : a ₁ , a ₂ ,..., a _m represent the weighted values of m index factors u _i calculated by formula (1); The function calculates the evaluation results of the i (i=1,2,...,m) index factor u _i for the attack method j (j=1,2,...,n) to be evaluated; b ₁ ,b ₂ ,... , b _n respectively represent the evaluation and quantification results of n attack methods to be evaluated, and the larger the value of b ₁ , b ₂ ,..., b _n is, the better the attack effect is.

As another preferred solution, the service information system attack effectiveness evaluation index factor set with labels in the present invention:

Firstly, the first-level evaluation index factor set is recorded as the label U={u ₁ u ₂ }; secondly, u _i (i=1,2) is further divided into the second-level evaluation index factor set u _i ={u _i1 u _i2 …u _ij }; thirdly, u _ij (i=1,2; j=1,2) is further divided into the third-level evaluation index factor set u _ij ＝{u _ij1 u _ij2 …u _ijp }; finally, Divide u _ijp (i=1,2; j=1,2; p=1,2,3) into fourth-level evaluation index factor set u _ijp ={u _ijp1 u _ijp2 … u _ijpq }; w _i , w _ij , w _ijp , and w _ijpq respectively represent the weights corresponding to the evaluation index factors at all levels, and their subscripts are the same as the subscripts of the corresponding index factors.

As another preferred solution, the present invention establishes the weight set of the four-dimensional weighting formula of the evaluation index factor sets at all levels; each weight set is determined by the formula (1) under the situation of setting the weighting preference factors α and β Calculated; the weight set of the four-dimensional weighting formula of the index factor sets at all levels is as follows;

In formula (6), the vectors beginning with A represent the weight vectors of index factor sets at all levels, and the variables beginning with A correspond to the weights of each evaluation index factor in the service information system attack effectiveness evaluation index factor set with a label, satisfying the relationship

Secondly, there are a total of 21 terminal evaluation index factors in the present invention, and the definitions are given below respectively;

(1) Host privilege escalation level membership function

It is a multivariate discrete scale, where x=0, 1, 2, 3, 4, 5 respectively represent the 6 levels of host privilege escalation levels from low to high;

(2) Membership function of the success time of privilege escalation

It is a continuous scale, where the preset parameter t represents the maximum privilege escalation success time that the attack can tolerate, and the independent variable x represents the actual privilege escalation success time of the attack;

(3) Membership function of authority stability time

It is a continuous scale, where the preset parameter t represents the maximum permission stabilization time expected by the attack, and the independent variable x represents the permission stabilization time actually obtained by the attack;

(4) Information resource damage membership function

It is a multivariate discrete scale, where x=0, 1, 2, 3, 4, 5 represent 6 levels of information resource damage from low to high;

(5) Membership function of host system paralysis

It is a binary discrete scale, where x=0 means that the attack did not cause the host system to be paralyzed, and x=1 means that the attack caused the host system to be paralyzed;

(6) Business function cheats membership function

It is a binary discrete scale, where x=0 means that the attack did not cause business function deception, and x=1 means that the attack caused business function deception;

(7) The host system takes over the membership function

It is a binary discrete scale, where x=0 means that the attack did not cause the host system to take over, and x=1 means that the attack caused the host system to take over;

(8) Membership function of information importance

It is a multivariate discrete scale, where x=0, 1, 2, 3, 4, 5 represent the 6 levels from low to high of the importance of information obtained by attacking;

(9) Membership function of information correct ratio

It is a continuous scale, where the preset parameter t represents the total amount of information expected to be obtained by the attack, and the independent variable x represents the amount of information actually obtained by the attack;

(10) Information extraction time membership function

It is a continuous scale, where the preset parameter t represents the maximum information extraction time that the attack can tolerate, and the independent variable x represents the actual information extraction time of the attack;

(11) Destruction success time membership function

It is a continuous scale, where the preset parameter t represents the maximum damage success time that the attack can tolerate, and the independent variable x represents the actual damage success time of the attack;

(12) Membership function of tampering success rate

It is a continuous scale, where the preset parameter t represents the total number of service tampering attacks, and the independent variable x represents the number of successful attacks on actual service tampering attacks;

(13) Counterfeit success rate membership function

It is a continuous scale, where the preset parameter t represents the total number of service spoofing attacks, and the independent variable x represents the number of successful attacking actual service spoofing attacks;

(14) Rejection success rate membership function

It is a continuous scale, where the preset parameter t represents the total number of denial-of-service attacks, and the independent variable x represents the number of successful denial-of-service attacks;

(15) Service degradation membership function

It is a multivariate discrete scale, where x=0, 1, 2, 3, 4, 5 respectively represent 6 levels of service degradation from low to high;

(16) Service termination membership function

It is a binary discrete scale, where x=0 means that the attack did not cause service termination, and x=1 means that the attack caused service termination;

(17) Service deception membership function

It is a binary discrete scale, where x=0 means that the attack did not cause service deception, and x=1 means that the attack caused service deception;

(18) Host computing resource damage membership function

It is a continuous scale, where the preset parameter t represents the maximum amount of host computing resource damage expected to be caused by the attack, and the independent variable x represents the actual amount of host computing resource damage caused by the attack;

(19) Host storage resource damage membership function

It is a continuous scale, where the preset parameter t represents the maximum amount of host storage resource damage expected to be caused by the attack, and the independent variable x represents the actual amount of host storage resource damage caused by the attack;

(20) Service bandwidth damage membership function

It is a continuous scale, where the preset parameter t represents the maximum amount of service bandwidth damage expected to be caused by the attack, and the independent variable x represents the actual amount of service bandwidth damage caused by the attack;

(21) Service delay damage membership function

It is a continuous scale, where the preset parameter t represents the maximum amount of service delay damage expected to be caused by the attack, and the independent variable x represents the actual amount of service delay damage caused by the attack.

In addition, the attack effectiveness comprehensive evaluation model of the service information system of the present invention is shown in FIG. 1 .

The vector starting with A represents the weight vector of index factor sets at all levels, and its composition is shown in formulas (6) and (7). The vectors starting with B represent the comprehensive evaluation result vectors at all levels, and their calculation methods are shown in formulas (2), (3), (4), and (5);

Symbolic meaning of comprehensive evaluation model of service-oriented information system attack effectiveness

The invention has beneficial effects.

The invention first establishes a multi-level evaluation index factor set of service-oriented information system attack effectiveness. Second, establish a four-dimensional weighting formula. Based on the four-dimensional weight determination methods—Delphi method, Analytic Hierarchy Process (AHP,Analytic Hierarchy Process) method, variation coefficient method and mean square error method to calculate the weight vectors of index factor sets at all levels, the formula adopts a first-level assignment method. Weighting preference factor α and secondary weighting preference factor β are used to comprehensively weight and calculate the weight vector of index factors at all levels. Third, establish the multi-scale membership function of the terminal evaluation index factors. Multi-scale membership functions include discrete-scale membership functions and continuous-scale membership functions. Discrete-scale membership functions can be divided into binary discrete-scale membership functions and multivariate discrete-scale membership functions. Finally, a comprehensive evaluation model of service-oriented information system attack effectiveness is established to realize single-factor evaluation and comprehensive evaluation of service-oriented information system attack effectiveness.

Description of drawings

Fig. 1 is a comprehensive evaluation model of service information system attack effectiveness of the present invention.

Detailed ways

1. Establish a multi-level evaluation index factor set for service-oriented information system attack effectiveness

The service-oriented information system attack effectiveness evaluation index factors with labels are as follows.

Firstly, the first-level evaluation index factor set is recorded as the label U={u ₁ u ₂ }; secondly, u _i (i=1,2) is further divided into the second-level evaluation index factor set u _i ={u _i1 u _i2 …u _ij }; thirdly, u _ij (i=1,2; j=1,2) is further divided into the third-level evaluation index factor set u _ij ＝{u _ij1 u _ij2 …u _ijp }; finally, U _ijp (i=1,2; j=1,2; p=1,2,3) is further divided into a fourth-level evaluation index factor set u _ijp ={u _ijp1 u _ijp2 . . . u _ijpq }. The service-oriented information system attack effectiveness evaluation index factors with labels are concentrated. w _i , w _ij , w _ijp , and w _ijpq respectively represent the weights corresponding to the evaluation index factors at all levels, and their subscripts are the same as the corresponding index factor subscripts same.

2. Establish a weight set based on the four-dimensional weighting formula

On the basis of the service-oriented information system attack effectiveness evaluation index factor set with labels, the weight set of the four-dimensional weighting formula of the evaluation index factor sets at all levels is established. Each weight set is calculated by formula (1) under the condition of setting weighting preference factors α and β. The weight set of the four-dimensional weighting formula of the index factor sets at all levels is as follows.

In formula (6), the vectors beginning with A represent the weight vectors of index factor sets at all levels, and the variables beginning with A correspond to the weights of each evaluation index factor in the service information system attack effectiveness evaluation index factor set with a label, satisfying the relationship

3. Establish the multi-scale membership function of each terminal evaluation index factor

The service information system attack effectiveness evaluation index factors with labels are concentrated, and there are 21 terminal evaluation index factors. The definitions are given below.

(1) Host privilege escalation level membership function

It is a multivariate discrete scale, where x=0, 1, 2, 3, 4, 5 respectively represent the 6 levels of host privilege escalation levels from low to high.

(2) Membership function of the success time of privilege escalation

It is a continuous scale, where the preset parameter t represents the maximum privilege escalation success time that the attack can tolerate, and the independent variable x represents the actual privilege escalation success time of the attack.

(3) Membership function of authority stability time

It is a continuous scale, where the preset parameter t represents the maximum authorization stabilization time expected by the attack, and the independent variable x represents the actual authorization stabilization time obtained by the attack.

(4) Information resource damage membership function

It is a multivariate discrete scale, where x=0, 1, 2, 3, 4, 5 represent 6 levels of damage to information resources from low to high.

(5) Membership function of host system paralysis

It is a binary discrete scale, where x=0 indicates that the attack did not cause the host system to be paralyzed, and x=1 indicates that the attack caused the host system to be paralyzed.

(6) Business function cheats membership function

It is a binary discrete scale, where x=0 means that the attack does not cause business function deception, and x=1 means that the attack causes business function deception.

(7) The host system takes over the membership function

It is a binary discrete scale, where x=0 indicates that the attack did not cause the host system to take over, and x=1 indicates that the attack caused the host system to take over.

(8) Membership function of information importance

It is a multivariate discrete scale, where x=0, 1, 2, 3, 4, 5 represent 6 levels from low to high of the importance of information obtained by attacking.

(9) Membership function of information correct ratio

It is a continuous scale, where the preset parameter t represents the total amount of information expected to be obtained by the attack, and the independent variable x represents the amount of information actually obtained by the attack.

(10) Information extraction time membership function

It is a continuous scale, where the preset parameter t represents the maximum information extraction time that the attack can tolerate, and the independent variable x represents the actual information extraction time of the attack.

(11) Destruction success time membership function

It is a continuous scale, where the preset parameter t represents the maximum damage success time that the attack can tolerate, and the independent variable x represents the actual damage success time of the attack.

(12) Membership function of tampering success rate

It is a continuous scale, where the preset parameter t represents the total number of service tampering attacks, and the independent variable x represents the number of successful service tampering attacks.

(13) Counterfeit success rate membership function

It is a continuous scale, where the preset parameter t represents the total number of service spoofing attacks, and the independent variable x represents the number of successful attacking actual service spoofing attacks.

(14) Rejection success rate membership function

It is a continuous scale, where the preset parameter t represents the total number of denial of service attacks, and the independent variable x represents the number of successful denial of service attacks.

(15) Service degradation membership function

It is a multivariate discrete scale, where x=0, 1, 2, 3, 4, 5 respectively represent 6 levels of service degradation from low to high.

(16) Service termination membership function

It is a binary discrete scale, where x=0 means that the attack did not cause service termination, and x=1 means that the attack caused service termination.

(17) Service deception membership function

It is a binary discrete scale, where x=0 indicates that the attack does not cause service deception, and x=1 indicates that the attack causes service deception.

(18) Host computing resource damage membership function

It is a continuous scale, where the preset parameter t represents the maximum amount of host computing resource damage expected to be caused by the attack, and the independent variable x represents the actual amount of host computing resource damage caused by the attack.

(19) Host storage resource damage membership function

It is a continuous scale, where the preset parameter t represents the maximum amount of host storage resource damage expected to be caused by the attack, and the independent variable x represents the actual amount of host storage resource damage caused by the attack.

(20) Service bandwidth damage membership function

It is a continuous scale, where the preset parameter t represents the maximum amount of service bandwidth damage expected to be caused by the attack, and the independent variable x represents the actual amount of service bandwidth damage caused by the attack.

(21) Service delay damage membership function

It is a continuous scale, where the preset parameter t represents the maximum amount of service delay damage expected to be caused by the attack, and the independent variable x represents the actual amount of service delay damage caused by the attack.

4. Establish a comprehensive evaluation model for service-oriented information system attack effectiveness

The comprehensive evaluation model of service information system attack effectiveness is shown in Figure 1.

The vector starting with A represents the weight vector of index factor sets at all levels, and its composition is shown in formulas (6) and (7). The vectors starting with B represent the vectors of comprehensive evaluation results at all levels, and their calculation methods are shown in formulas (2), (3), (4), and (5). The meanings of each symbol in the comprehensive evaluation model of service-oriented information system attack effectiveness are as follows.

It can be understood that the above specific descriptions of the present invention are only used to illustrate the present invention and are not limited to the technical solutions described in the embodiments of the present invention. Those of ordinary skill in the art should understand that the present invention can still be modified or Equivalent replacements to achieve the same technical effect; as long as they meet the needs of use, they are all within the protection scope of the present invention.

Claims (1)

1. A comprehensive evaluation method for service-oriented information system attack effectiveness, which is characterized in that it includes the following steps: 1) Establish a multi-level evaluation index factor set for service-oriented information system attack effectiveness; 2) Establish a weight set based on the four-dimensional weighting formula; 3) Establish the multi-scale membership function of the terminal evaluation index factors; 4) Establish a comprehensive evaluation model of service-oriented information system attack effectiveness; Said step 2) the weighting formula is input by the index factor set weight vector calculated respectively by Delphi method, AHP method, variation coefficient method and mean square error method, through the first-level weighting preference factor α, 0≤α≤1 and the second-level weighting The weight preference factor β, 0≤β≤1 to comprehensively weight and calculate the weight set A, A＝αβD _w +α(1-β)A _w +(1-α)(V _w +S _w ) (1) In formula (1), 0≤α≤1, 0≤β≤1, D _w , A _w , V _w and S _w respectively represent the index factors calculated by Delphi method, AHP method, variation coefficient method and mean square error method Set the weight vector; the first-level weighting preference factor α is greater than 0.5, indicating that the evaluation is biased towards subjective weighting; when α≠0, the second-level weighting preference factor β is greater than 0.5, indicating that the Delphi method and the AHP method are more weighted by the Delphi method ; The larger α and β indicate more emphasis on subjective weighting, the smaller α and β indicate more emphasis on objective weighting; when α=0, formula (1) fully adopts objective weighting; when α=1, formula (1) Fully adopt subjective weighting; when α=1, β=0, formula (1) completely adopts AHP method for weighting; when α=1, β=1, formula (1) completely adopts Delphi method for weighting ; The step 1) multi-level evaluation index factor set of service-oriented information system attack effectiveness is:

The step 3) terminal evaluation index factor refers to the index factor represented by the terminal node in the tree structure of the evaluation index factor set; the multi-scale membership function of the terminal evaluation index factor can be divided into a discrete scale membership function and a continuous scale membership function, Discrete scale membership functions are divided into binary discrete scale membership functions and multivariate discrete scale membership functions; the return value of the continuous scale membership function is any real number in the interval [0, 1]; the return value of the binary discrete scale membership function is an integer 0 or 1; The return value of the multivariate discrete scale membership function is a plurality of discrete real numbers in the interval [0, 1]; The step 4) first establishes a single-factor evaluation model of service-oriented information system attack effectiveness; single-factor evaluation refers to evaluating from one factor alone, and using the multi-scale membership function of the terminal index factor to calculate the attack method j to be evaluated, j= 1, 2,..., n are respectively the evaluation result vectors of i, i=1, 2,..., m index factors u _i R _i =(r _i1 ,r _i2 ,…,r _in ),i=1,2,…,m (2) Form each single factor evaluation result vector into a row matrix

Use the weight set of the four-dimensional weighting formula for each column of the single-factor evaluation matrix R A＝(a ₁ ,a ₂ ,…,a _m ) (4) Carry out a weighted average to obtain a comprehensive evaluation vector

Indicates the attack effectiveness evaluation results of n attack methods when m index factors are integrated; In formula (4) and formula (5): a ₁ , _{a 2} ,..., a _m represent the weighted values of m index factors u _i calculated by formula (1); Scale membership function calculation The attack method j,j=1,2,...,n to be evaluated evaluates the i,i=1,2,...,m index factors u _i respectively; b ₁ ,b ₂ ,... , b _n respectively represent the evaluation and quantification results of the n attack methods to be evaluated, and the larger the value of b ₁ , b ₂ ,..., b _n is, the better the attack effect is; The service-oriented information system attack effectiveness evaluation index factor set with labels: Firstly, the first-level evaluation index factor set is recorded as the label U={u ₁ u ₂ }; secondly, u ₁ and u ₂ are further divided into the second-level evaluation index factor set, where u ₁ ={u ₁₁ ,u ₁₂ }, u ₂ ＝{u ₂₁ ,u ₂₂ }; thirdly, further divide u _kl ,k=1,2,l=1,2 into the third-level evaluation index factor set u _kl ＝{u _kl1 u _kl2 … u _klp }; Finally, further divide u _klp ,k=1,2,l=1,2,p=1,2,3 into the fourth-level evaluation index factor set u _klp ＝{u _klp1 u _klp2 …u _klpq }; w _k , w _kl , w _klp , w _klpq respectively represent the weights corresponding to the evaluation index factors at all levels, and their subscripts are the same as the subscripts of the corresponding index factors; Establish the weight set of the four-dimensional weighting formula of the evaluation index factor sets at all levels; each weight set is calculated by formula (1) under the condition of setting the weighting preference factors α and β; the four-dimensional weighting formula of the index factor sets at all levels The weight set of the dimension weighting formula is as follows;

In formula (6), the vectors beginning with A represent the weight vectors of index factor sets at all levels, and the variables beginning with A correspond to the weights of each evaluation index factor in the service information system attack effectiveness evaluation index factor set with a label, satisfying the relationship

There are a total of 21 terminal evaluation index factors, and the definitions are given below; (1) Host privilege escalation level membership function

It is a multivariate discrete scale, where x ₁ = 0, 1, 2, 3, 4, 5 respectively represent the 6 levels of host privilege escalation levels from low to high; (2) Membership function of the success time of privilege escalation

It is a continuous scale, where the preset parameter t ₂ represents the maximum privilege escalation success time that the attack can tolerate, and the independent variable x ₂ represents the actual privilege escalation success time of the attack; (3) Membership function of authority stability time

It is a continuous scale, where the preset parameter _t3 represents the maximum permission stabilization time expected by the attack, and the independent variable _x3 represents the permission stabilization time actually obtained by the attack; (4) Information resource damage membership function

It is a multivariate discrete scale, where x ₄ = 0, 1, 2, 3, 4, 5 represent 6 levels of damage to information resources from low to high; (5) Membership function of host system paralysis

Belongs to a binary discrete scale, where x ₅ = 0 means that the attack did not cause the host system to be paralyzed, and x ₅ = 1 means that the attack caused the host system to be paralyzed; (6) Business function cheats membership function

Belongs to a binary discrete scale, where x ₆ =0 means that the attack did not cause business function deception, and x ₆ =1 means that the attack caused business function deception; (7) The host system takes over the membership function

Belongs to a binary discrete scale, where x ₇ = 0 means that the attack did not cause the host system to take over, and x ₇ = 1 means that the attack caused the host system to take over; (8) Membership function of information importance

It belongs to multivariate discrete scale, where x ₈ =0, 1, 2, 3, 4, 5 represent 6 levels from low to high of the importance of information obtained by attack; (9) Membership function of information correct ratio

It is a continuous scale, where the preset parameter _t9 represents the total amount of information expected to be obtained by the attack, and the independent variable _x9 represents the amount of information actually obtained by the attack; (10) Information extraction time membership function

It is a continuous scale, where the preset parameter t ₁₀ represents the maximum information extraction time that the attack can tolerate, and the independent variable x ₁₀ represents the actual information extraction time of the attack; (11) Destruction success time membership function

It is a continuous scale, where the preset parameter t ₁₁ represents the maximum damage success time that the attack can tolerate, and the independent variable x ₁₁ represents the actual damage success time of the attack; (12) Membership function of tampering success rate

It is a continuous scale, wherein the preset parameter t ₁₂ represents the total number of times of service tampering attacks, and the independent variable x ₁₂ represents the number of successful attacks on actual service tampering attacks; (13) Counterfeit success rate membership function

It is a continuous scale, wherein the preset parameter t ₁₃ represents the total number of service counterfeiting attacks, and the independent variable x ₁₃ represents the number of successful attacks against actual service counterfeiting attacks; (14) Rejection success rate membership function

It is a continuous scale, wherein the preset parameter _t14 represents the total number of denial-of-service attacks, and the independent variable _x14 represents the number of successful denial-of-service attacks; (15) Service degradation membership function

It is a multivariate discrete scale, where x ₁₅ = 0, 1, 2, 3, 4, 5 respectively represent 6 levels of service degradation from low to high; (16) Service termination membership function

It is a binary discrete scale, where x ₁₆ = 0 means that the attack did not cause service termination, and x ₁₆ = 1 means that the attack caused service termination; (17) Service deception membership function

Belongs to a binary discrete scale, where x ₁₇ =0 indicates that the attack does not cause service deception, and x ₁₇ =1 indicates that the attack causes service deception; (18) Host computing resource damage membership function

It is a continuous scale, where the preset parameter t ₁₈ represents the maximum amount of host computing resource damage expected to be caused by the attack, and the independent variable x ₁₈ represents the actual amount of host computing resource damage caused by the attack; (19) Host storage resource damage membership function

It is a continuous scale, where the preset parameter t ₁₉ represents the maximum amount of host storage resource damage expected to be caused by the attack, and the independent variable x ₁₉ represents the actual amount of host storage resource damage caused by the attack; (20) Service bandwidth damage membership function

It is a continuous scale, where the preset parameter t ₂₀ represents the maximum amount of service bandwidth damage expected to be caused by the attack, and the independent variable x ₂₀ represents the actual amount of service bandwidth damage caused by the attack; (21) Service delay damage membership function

It is a continuous scale, where the preset parameter t ₂₁ represents the maximum amount of service delay damage expected to be caused by the attack, and the independent variable x ₂₁ represents the actual amount of service delay damage caused by the attack.

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