CN111768057A - DAS protection effect evaluation method and device - Google Patents
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Abstract
The embodiment of the invention provides a method and a device for evaluating the DAS protection effect, wherein the method comprises the steps of constructing an evaluation index system comprising multi-level evaluation indexes; calculating the weight of each next-level evaluation index to the previous-level evaluation index in the evaluation index system; dividing the protection effect into a plurality of grades, and for any one upper-level evaluation index, calculating the membership degree of each lower-level evaluation index of the upper-level evaluation index to the protection effect grade; obtaining a fuzzy evaluation vector of the previous-level evaluation index according to the weight of each next-level evaluation index to the previous-level evaluation index and the membership degree of each next-level evaluation index to the protection effect grade; the embodiment of the invention realizes the comprehensive evaluation of the safety protection effect and provides a basis for the improvement and perfection of the network safety protection scheme of the distribution automation system.
Description
Technical Field
The embodiment of the invention relates to the technical field of power distribution networks, in particular to a DAS protection effect evaluation method.
Background
The power distribution network is used as an important component of a power network and plays an important role in the development process of the smart power grid. Safety is the premise of reliable and stable operation of a power Distribution network, and a Distribution Automation System (DAS) is an industrial control system for ensuring safe, stable, reliable and economic operation of the power Distribution network, is an automation system for realizing operation monitoring and control of the power Distribution network, has functions of SCADA (supervisory control and data acquisition), fault processing, analysis application, interconnection with related application systems and the like, and mainly comprises a Distribution automation system master station (for short, a Distribution master station), a Distribution automation terminal (for short, a Distribution terminal) and a communication network. With the construction and development of the DAS, security events caused by network attacks occur frequently, and serious influence is generated on the power industry.
However, for the existing DAS, there is no objective and practical index system and method for evaluating the protection effect. Therefore, an evaluation index system is urgently needed to be constructed, research on the DAS network security protection effect evaluation method is developed, and a set of network security protection effect evaluation system suitable for DAS is formed. The method aims to provide basis for improvement and perfection of a protection scheme, so that safe and reliable operation of a power grid is supported.
Disclosure of Invention
Embodiments of the present invention provide a method and an apparatus for evaluating DAS protective effects, which overcome or at least partially solve the above problems.
In a first aspect, an embodiment of the present invention provides a method for evaluating a DAS protective effect, including:
constructing an evaluation index system comprising a plurality of levels of evaluation indexes;
calculating the weight of each next-level evaluation index to the previous-level evaluation index in the evaluation index system;
dividing the protection effect into a plurality of grades, and calculating the membership degree of each next-level evaluation index of the previous-level evaluation indexes to the protection effect grade for any previous-level evaluation index;
for each upper-level evaluation index, obtaining a fuzzy evaluation vector of the upper-level evaluation index according to the weight of each lower-level evaluation index to the upper-level evaluation index and the membership degree of each lower-level evaluation index to the protection effect grade;
determining the level of the DAS protection effect according to the fuzzy evaluation vector of the top-level evaluation index and the absolute difference of a pre-constructed ideal evaluation matrix;
the fuzzy evaluation vector is used for representing the membership degree of the corresponding previous-level evaluation index to the protection effect grade, the ideal evaluation matrix is an identity matrix, and the jth row element is used for representing the membership degree of the top-level evaluation index to the jth protection effect in an ideal state.
In a second aspect, an embodiment of the present invention provides an apparatus for evaluating a DAS protective effect, including:
the system construction module is used for constructing an evaluation index system comprising multi-level evaluation indexes;
the weight calculation module is used for calculating the weight of each next-level evaluation index in the evaluation index system to the previous-level evaluation index;
the membership calculation module is used for dividing the protection effect into a plurality of grades, and calculating the membership of each next-level evaluation index of the previous-level evaluation indexes to the protection effect grade for any previous-level evaluation index;
the fuzzy evaluation vector calculation module is used for obtaining a fuzzy evaluation vector of each upper-level evaluation index according to the weight of each lower-level evaluation index on the upper-level evaluation index and the membership degree of each lower-level evaluation index on the protection effect grade;
the grade determining module is used for determining the grade of the DAS protection effect according to the fuzzy evaluation vector of the top-grade evaluation index and the absolute difference of a pre-constructed ideal evaluation matrix;
the fuzzy evaluation vector is used for representing the membership degree of the corresponding previous-level evaluation index to the protection effect grade, the ideal evaluation matrix is an identity matrix, and the jth row element is used for representing the membership degree of the top-level evaluation index to the jth protection effect in an ideal state
In a third aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method provided in the first aspect when executing the program.
In a fourth aspect, an embodiment of the present invention provides a non-transitory computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the method as provided in the first aspect.
The DAS protection effect evaluation method and device provided by the embodiment of the invention comprehensively consider the power distribution master station, the power distribution terminal, the communication network, the boundary and other layers, can comprehensively measure the protection effect, adopts an analytic hierarchy process to calculate the index weight, can quantize the result of qualitative analysis, and is easy to realize. Based on the established evaluation index system, the relevance between the evaluation object and the ideal evaluation vector is calculated by adopting an improved fuzzy comprehensive evaluation method, the calculation result can objectively and accurately reflect the protection effect grade, the comprehensive evaluation on the safety protection effect is realized, and a basis is provided for the improvement and the perfection of the network safety protection scheme of the power distribution automation system.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for evaluating DAS protective effects according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a power distribution automation system network safety protection effect evaluation index system according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a device for evaluating the DAS protective effect according to an embodiment of the present invention;
fig. 4 is a schematic physical structure diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart of a method for evaluating DAS shielding effectiveness according to an embodiment of the present invention, and as shown in fig. 1, the method includes steps S101, S102, S103, S104, and S105, specifically,
and S101, constructing an evaluation index system comprising a multi-level evaluation index.
Specifically, according to the DAS business process and system architecture characteristics, network security risk analysis is performed on 4 levels of a power distribution terminal, a communication channel, a power distribution main station and a boundary, evaluation indexes are reasonably selected by combining an adopted safety protection scheme, and an evaluation index system is constructed.
Fig. 2 is a schematic diagram of an evaluation index system for a network security protection effect of a power distribution automation system according to an embodiment of the present invention, and as shown in fig. 2, a target layer of the evaluation index system is a DAS network security protection effect and belongs to a top-level evaluation index; the first-level evaluation index (first-level index for short) is the safety protection effect of the power distribution main station, the power distribution terminal, the communication network and the boundary.
Aiming at a power distribution main station, the embodiment of the invention provides 4 items of two-level evaluation indexes (for short, two-level evaluation indexes) of identity authentication, data security, host security protection and access control.
Aiming at the power distribution terminal, the embodiment of the invention provides and selects 7 secondary indexes of identity authentication, physical safety protection, self safety protection, interaction with an on-site operation and maintenance tool, data safety, malicious code prevention and intrusion prevention.
Aiming at a communication network, the embodiment of the invention provides 7 secondary indexes of access authentication, a communication mode, network isolation, access control, data security, equipment protection and network attack protection.
Aiming at the boundary, the embodiment of the invention provides 5 items of secondary indexes of intrusion prevention, malicious code prevention, access control, audit and boundary isolation.
S102, calculating the weight of each next-level evaluation index to the previous-level evaluation index in the evaluation index system.
Specifically, in the embodiment of the present invention, the weight may be determined empirically by an expert in the DAS security protection field, and in order to objectively and accurately determine the weight of the next-level evaluation index to the previous-level evaluation index, the embodiment of the present invention may perform analysis by using an operation theory, such as an analytic hierarchy process, a fuzzy method, a fuzzy analytic hierarchy process, and an expert evaluation method. As a preferred embodiment, the embodiment of the present invention uses an Analytic Hierarchy Process (AHP) to perform analysis, where the AHP is a decision-making method that decomposes elements always related to decision-making into a hierarchy of targets, criteria, schemes, and the like, and performs qualitative and quantitative analysis based on the hierarchy. Note that, the weight of the next-level evaluation index to the previous-level evaluation index, that is, the degree of importance of the next-level evaluation index to the previous-level evaluation index, is 1 in the sum of the weights of all the next-level evaluation indexes of the previous-level evaluation index.
S103, dividing the protection effect into a plurality of grades, and calculating the membership degree of each next-level evaluation index of the previous-level evaluation indexes to the protection effect grade for any previous-level evaluation index.
Specifically, on the basis of the above steps, the embodiment of the present invention adopts a fuzzy comprehensive evaluation method to calculate the degree of membership of each next-level evaluation index of the previous-level evaluation index to the protection effect level. The comprehensive evaluation method converts qualitative evaluation into quantitative evaluation according to the membership theory of fuzzy mathematics, namely, fuzzy mathematics is used for making overall evaluation on objects or objects restricted by various factors. The method has the characteristics of clear result and strong systematicness, can better solve the problems of fuzziness and difficult quantization, and is suitable for solving various non-determinacy problems.
The discrimination and quantification of the membership degree in the embodiment of the invention can be determined by a linear membership degree function based on the practical situation implemented by the expert based on DAS safety protection measures. It can be understood that, for a next-level evaluation index, the sum of the membership degrees of the next-level evaluation index to all the protection effect levels is 1.
And S104, for each upper-level evaluation index, obtaining a fuzzy evaluation vector of the upper-level evaluation index according to the weight of each lower-level evaluation index to the upper-level evaluation index and the membership degree of each lower-level evaluation index to the protection effect grade.
Specifically, if a certain upper-level evaluation index A has 3 lower-level evaluation indexes a, b and c, the protection effect grades are divided into three grades, namely A, B and C; if the weights of a, b and c to a are 0.2, 0.3 and 0.5 respectively, the membership degrees of a to the protection effect grade are 1, 0 and 0, the membership degrees of b to the protection effect grade are 0,1 and 0, and the membership degrees of c to the protection effect grade are 1, 0 and 0, then the fuzzy evaluation vector of a can be calculated by adopting the following formula:
obviously, the fuzzy evaluation vector is used to represent the degree of membership of the previous evaluation index to the protection effect level, and from the above results, the evaluation index a has a degree of membership of 0.7 for the protection effect level a, a degree of membership of 0.3 for the protection effect level b, and a degree of membership of 0 for the protection effect level a. Obviously, the fuzzy evaluation vectors of all the evaluation indexes, that is, the membership degree of the protection effect level, can be deduced layer by layer through step S104.
And S105, determining the level of the DAS protection effect according to the fuzzy evaluation vector of the top-level evaluation index and the absolute difference of a pre-constructed ideal evaluation matrix. The ideal evaluation matrix is an identity matrix, and the mth row element is used for representing the membership degree of the top-level evaluation index to the mth level protection effect in the ideal state.
When an evaluation vector P is given (P ═ P)1,p2,…,pn) Wherein p isjTo evaluate the membership degree of the index belonging to the class j
If the z-th component of the evaluation vector P is the largest, the evaluation index is considered to belong approximately to the class VZThus giving an ideal evaluation vector Pz(…,1, …) where the z-th component is 1. The ideal evaluation matrix is composed of m rows of ideal evaluation vectors.
The embodiment of the invention divides the evaluation result into five grades, so the set ideal evaluation vector is P1＝(1,0,0,0,0)，P2＝(0,1,0,0,0)，P3＝(0,0,1,0,0)，P4＝(0,0,0,1,0)，P5(0,0,0,0,1), constituting an ideal evaluation matrix, as in table 3:
table 3 table of ideal evaluation matrices of the embodiments of the present invention
For the mth row element of the ideal evaluation matrix, the absolute difference delta between each element in the mth row and the corresponding element in the fuzzy evaluation vector B is calculatedmjWherein j represents the j-th column element in the ideal evaluation matrix and the fuzzy evaluation vector;
calculating the correlation coefficient theta between the fuzzy evaluation vector B and each element of the mth row according to the following formulamj：
Wherein, DeltamaxRepresents the maximum absolute difference, Δ, between all elements in the ideal evaluation matrix and the corresponding element in the fuzzy evaluation vector BminRepresenting the minimum absolute difference between all elements in the ideal evaluation matrix and the corresponding elements in the fuzzy evaluation vector B, and α is 0.5;
according to the formula
Determining the relevance sigma of the fuzzy evaluation vector B and the mth row element of the ideal evaluation matrixBVm(ii) a It is to be understood that; the mth row element of the ideal evaluation matrix is used for representing the mth evaluation effect level, and the relevance of the fuzzy evaluation vector B and the mth row element of the ideal evaluation matrix is calculated, which means that the relevance of the top-level evaluation index and the mth evaluation effect is calculated.
And (5) counting the relevance between the fuzzy evaluation vector B and all the protection effect grades, and taking the protection effect grade corresponding to the maximum relevance as the grade of the DAS protection effect.
It should be noted that, the embodiments of the present invention comprehensively consider the power distribution master station, the power distribution terminal, the communication network, the boundary, and other layers, so that the protection effect can be more comprehensively measured, and the index weight is calculated by using the analytic hierarchy process, so that the result of the qualitative analysis can be quantized and easily implemented. Based on the established evaluation index system, the relevance between the evaluation object and the ideal evaluation vector is calculated by adopting an improved fuzzy comprehensive evaluation method, the calculation result can objectively and accurately reflect the protection effect grade, the comprehensive evaluation on the safety protection effect is realized, and a basis is provided for the improvement and the perfection of the network safety protection scheme of the power distribution automation system.
On the basis of the above embodiments, as an optional embodiment, calculating the weight of each next-level evaluation index to the previous-level evaluation index in the evaluation index system specifically includes:
constructing a plurality of judgment matrixes according to the series of the evaluation index system, wherein the judgment matrixes are used for representing the importance degree ratio of every two next-level evaluation indexes in all the next-level evaluation indexes aiming at the same previous-level evaluation index;
and carrying out consistency check on the judgment matrix, and if the consistency check is met, carrying out normalization processing on the eigenvector corresponding to the maximum eigenvalue of the judgment matrix to obtain the weight of each next-level evaluation index in the judgment matrix to the previous-level evaluation index.
Specifically, in the embodiment of the present invention, the importance degrees of the next-level evaluation indexes are compared pairwise, and a judgment matrix a ═ a is constructed by experts in the DAS safety protection field according to a scale of 1 to 9 (as shown in table 1)ij]n×nWherein a isijThe ratio of the importance of the next-level evaluation indexes i and j to the evaluation object is shown, and n represents the number of the next-level evaluation indexes.
TABLE 1 Scale Table of importance of evaluation index
For example, if a21A number of 5 indicates that the effect of the evaluation index 2 on the higher-order evaluation index is significantly more important than the effect of the evaluation index 1, and if a23A value of 4 indicates that the effect of the evaluation index 2 on the higher-order evaluation index than that of the evaluation index 3 is between significantly important and strongly important, and accordingly, a is defined12Is 1/5, the reciprocal of 5, a32Is 1/4.
On the basis of the foregoing embodiments, as an optional embodiment, the consistency check is performed on the determination matrix, specifically:
the consistency index CI is calculated according to the following formula:
wherein n is the number of next-level evaluation indexes of the previous-level evaluation indexes corresponding to the judgment matrix, and lambdamaxRepresenting the maximum eigenvalue of the decision matrix.
If CI is 0, judging that the matrix has complete consistency, otherwise, calculating a random consistency ratio CR:
wherein RI is an average random consistency index (the value is shown in table 2, and n in the table is the number of next-level evaluation indexes of the previous-level evaluation indexes corresponding to the determination matrix).
TABLE 2 average random consistency index RI
And when CR is less than or equal to 0.10, judging that the matrix meets the consistency, otherwise, adjusting the value of elements in the judgment matrix and judging the consistency again until the consistency is met.
And calculating the maximum eigenvalue of the judgment matrix meeting the consistency check and the eigenvector corresponding to the maximum eigenvalue, and normalizing the eigenvector to obtain the required weight. According to the definition of the characteristic value, the number of elements of the characteristic value is consistent with the number of the next-level evaluation indexes.
Because the object to be evaluated in the embodiment of the invention relates to multiple factors and multiple levels, the embodiment of the invention provides an improved fuzzy comprehensive evaluation method, which mainly comprises the following steps:
(1) determining a set of factors and a weight vector
Determining a factor set U and a weight W according to an evaluation index system, taking the evaluation index system of the network safety protection effect of the distribution automation system shown in fig. 2 as an example, where the primary index factor set is U ═ W1,U2,…Ui,…UlThe factor set of the secondary index is Ui＝{Ui1,Ui2,…UiTAnd the weight vector of the primary evaluation index is as follows: w ═ W1,w2,…wlW is the secondary index weight vectori＝{wi1,wi2,…wiTTherein ofL represents the number of the first-level index factors, T represents the number of the second-level index factors under the corresponding first-level index factors,
(2) determining an evaluation set
Dividing the protection effect into five grades of good, general, poor and poor (good, general, poor and poor are 1, 2, 3, 4 and 5 in sequence), and determining an evaluation set as V ═ V1,V2,V3,V4,V5Quantized into scores { X }1,X2,X3,X4,X5100,80,60,40,20, and the level difference θ is 20.
(3) Calculating membership degree and constructing judgment matrix
Constructing a judgment matrix R of one first-level indexiSuch as
Wherein r isijAnd the membership degree of the ith next-level evaluation index to the jth evaluation grade is represented, T represents the number of next-level evaluation indexes of the previous-level evaluation index i, and J represents the number of protection effect grades.
The discrimination and quantification of the membership degree can be determined by a linear membership degree function, wherein a score x is given by an expert based on the actual situation implemented by DAS safety protection measures.
The next-level evaluation index x belongs to the membership degree of the 1 st protection effect grade:
the next-level evaluation index x belongs to the membership degree of the jth protective effect grade (1< J < J):
the next-level evaluation index x belongs to the membership degree of the J-th protection effect grade:
wherein, XjA score representing the jth level of protection effectiveness; θ represents the difference of the scores of the adjacent two protection effect levels.
(4) Determining fuzzy evaluation vector and ideal evaluation matrix
Calculating a fuzzy evaluation vector of a primary index:
Bi＝Wi·Ri
from BiForm a target layer judgment matrix
The blur evaluation vector B of the target layer (i.e., the top layer) is calculated as (B)01,b02,…,b0j,…,b0J)：b0jAnd (3) the evaluation index representing the top level belongs to the membership degree of the j-th level protection effect:
B＝W·R
(5) calculating the correlation coefficient
Calculating the absolute difference delta between the ideal evaluation matrix and the fuzzy evaluation vector BmjWherein m represents the mth row element;
Δmj＝|pmj-b0j|
find out the maximum difference value deltamaxAnd a minimum difference value deltaminCalculating the correlation coefficient thetamj：
Wherein α may be 0.5.
(6) Determining rating
Calculating the relevance degree sigma of the fuzzy evaluation phasor and the ideal evaluation vectorBVm：
Finding the maximumThe degree of association is determined, thereby determining the evaluation grade V of the network safety protection effect of the distribution automation systemm。
Fig. 3 is a schematic structural diagram of an apparatus for evaluating DAS shielding effectiveness according to an embodiment of the present invention, and as shown in fig. 3, the apparatus for evaluating DAS shielding effectiveness includes: the system comprises a system building module 301, a weight calculating module 302, a membership calculating module 303, a fuzzy evaluation vector calculating module 304 and a grade determining module 305, wherein:
the system construction module 301 is configured to construct an evaluation index system including multiple levels of evaluation indexes;
the weight calculation module 302 is configured to calculate a weight of each next-level evaluation index in the evaluation index system to the previous-level evaluation index;
the membership calculation module 303 is configured to divide the protection effect into a plurality of grades, and calculate, for any one previous-level evaluation index, a membership of each next-level evaluation index of the previous-level evaluation index to the protection effect grade;
the fuzzy evaluation vector calculation module 304 is configured to, for each previous-level evaluation index, obtain a fuzzy evaluation vector of the previous-level evaluation index according to the weight of each next-level evaluation index on the previous-level evaluation index and the membership degree of each next-level evaluation index on the protection effect level;
a grade determining module 305, configured to determine a grade of the DAS protection effect according to a fuzzy evaluation vector of the top-grade evaluation index and an absolute difference of a pre-constructed ideal evaluation matrix;
the fuzzy evaluation vector is used for representing the membership degree of the corresponding previous-level evaluation index to the protection effect grade, the ideal evaluation matrix is an identity matrix, and the jth row element is used for representing the membership degree of the top-level evaluation index to the jth protection effect in an ideal state.
The DAS protection effect evaluation apparatus provided in the embodiment of the present invention specifically executes the above-described DAS protection effect evaluation method embodiment flows, and please refer to the above-described DAS protection effect evaluation method embodiments for details, which are not described herein again. The DAS protection effect evaluation device provided by the embodiment of the invention comprehensively considers the power distribution master station, the power distribution terminal, the communication network, the boundary and other layers, can comprehensively measure the protection effect, adopts an analytic hierarchy process to calculate the index weight, can quantize the result of qualitative analysis, and is easy to realize. Based on the established evaluation index system, the relevance between the evaluation object and the ideal evaluation vector is calculated by adopting an improved fuzzy comprehensive evaluation method, the calculation result can objectively and accurately reflect the protection effect grade, the comprehensive evaluation on the safety protection effect is realized, and a basis is provided for the improvement and the perfection of the network safety protection scheme of the power distribution automation system.
Fig. 4 is a schematic entity structure diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 4, the electronic device may include: a processor (processor)410, a communication Interface 420, a memory (memory)430 and a communication bus 440, wherein the processor 410, the communication Interface 420 and the memory 430 are communicated with each other via the communication bus 440. The processor 410 may call a computer program stored in the memory 430 and executable on the processor 410 to perform the method for evaluating the DAS safeguard effect provided by the above embodiments, for example, including: constructing an evaluation index system comprising a plurality of levels of evaluation indexes; calculating the weight of each next-level evaluation index to the previous-level evaluation index in the evaluation index system; dividing the protection effect into a plurality of grades, and calculating the membership degree of each next-level evaluation index of the previous-level evaluation indexes to the protection effect grade for any previous-level evaluation index; for each upper-level evaluation index, obtaining a fuzzy evaluation vector of the upper-level evaluation index according to the weight of each lower-level evaluation index to the upper-level evaluation index and the membership degree of each lower-level evaluation index to the protection effect grade; determining the level of the DAS protection effect according to the fuzzy evaluation vector of the top-level evaluation index and the absolute difference of a pre-constructed ideal evaluation matrix; the fuzzy evaluation vector is used for representing the membership degree of the corresponding previous-level evaluation index to the protection effect grade, the ideal evaluation matrix is an identity matrix, and the jth row element is used for representing the membership degree of the top-level evaluation index to the jth protection effect in an ideal state.
In addition, the logic instructions in the memory 430 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or make a contribution to the prior art, or may be implemented in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
An embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to, when executed by a processor, perform the method for evaluating the DAS protection effect provided in the foregoing embodiments, for example, the method includes: constructing an evaluation index system comprising a plurality of levels of evaluation indexes; calculating the weight of each next-level evaluation index to the previous-level evaluation index in the evaluation index system; dividing the protection effect into a plurality of grades, and calculating the membership degree of each next-level evaluation index of the previous-level evaluation indexes to the protection effect grade for any previous-level evaluation index; for each upper-level evaluation index, obtaining a fuzzy evaluation vector of the upper-level evaluation index according to the weight of each lower-level evaluation index to the upper-level evaluation index and the membership degree of each lower-level evaluation index to the protection effect grade; determining the level of the DAS protection effect according to the fuzzy evaluation vector of the top-level evaluation index and the absolute difference of a pre-constructed ideal evaluation matrix; the fuzzy evaluation vector is used for representing the membership degree of the corresponding previous-level evaluation index to the protection effect grade, the ideal evaluation matrix is an identity matrix, and the jth row element is used for representing the membership degree of the top-level evaluation index to the jth protection effect in an ideal state.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for evaluating the DAS protection effect is characterized by comprising the following steps:
constructing an evaluation index system comprising a plurality of levels of evaluation indexes;
calculating the weight of each next-level evaluation index to the previous-level evaluation index in the evaluation index system;
dividing the protection effect into a plurality of grades, and calculating the membership degree of each next-level evaluation index of the previous-level evaluation indexes to the protection effect grade for any previous-level evaluation index;
for each upper-level evaluation index, obtaining a fuzzy evaluation vector of the upper-level evaluation index according to the weight of each lower-level evaluation index to the upper-level evaluation index and the membership degree of each lower-level evaluation index to the protection effect grade;
determining the level of the DAS protection effect according to the fuzzy evaluation vector of the top-level evaluation index and the absolute difference of a pre-constructed ideal evaluation matrix;
the fuzzy evaluation vector is used for representing the membership degree of the corresponding previous-level evaluation index to the protection effect grade, the ideal evaluation matrix is an identity matrix, and the jth row element is used for representing the membership degree of the top-level evaluation index to the jth protection effect in an ideal state.
2. The evaluation method according to claim 1, wherein the calculating of the weight of each next-level evaluation index to the previous-level evaluation index in the evaluation index system specifically comprises:
constructing a plurality of judgment matrixes according to the series of the evaluation index system, wherein the judgment matrixes are used for representing the importance degree ratio of every two next-level evaluation indexes in all the next-level evaluation indexes aiming at the same previous-level evaluation index;
and carrying out consistency check on the judgment matrix, and if the consistency check is met, carrying out normalization processing on the eigenvector corresponding to the maximum eigenvalue of the judgment matrix to obtain the weight of each next-level evaluation index in the judgment matrix to the previous-level evaluation index.
3. The evaluation method according to claim 2, wherein the consistency check of the judgment matrix specifically comprises:
the consistency index CI is calculated according to the following formula:
wherein n is the number of next-level evaluation indexes of the previous-level evaluation indexes corresponding to the judgment matrix, and lambdamaxRepresenting the maximum eigenvalue of the judgment matrix;
if the CI is equal to 0, determining that the judgment matrix passes consistency check;
if CI is not equal to 0, then the consistency ratio CR is calculated according to the following equation:
wherein, RI is a predetermined average random consistency index; and if CR is less than or equal to 0.1, determining that the judgment matrix passes consistency check.
4. The evaluation method according to claim 1, wherein for any one previous-level evaluation index, calculating the membership degree of each next-level evaluation index of the previous-level evaluation index to the protection effect level specifically comprises:
the next-level evaluation index x belongs to the membership degree of the 1 st protection effect grade:
the next-level evaluation index x belongs to the membership degree of the jth protective effect grade (1< J < J):
the next-level evaluation index x belongs to the membership degree of the J-th protection effect grade:
wherein, XjA score representing the jth level of protection effectiveness; θ represents the difference of the scores of the adjacent two protection effect levels.
5. The evaluation method according to claim 1, wherein the obtaining of the fuzzy evaluation vector of the previous-level evaluation index according to the weight of each next-level evaluation index on the previous-level evaluation index and the membership of each next-level evaluation index on the protection effect level specifically comprises:
for any one upper-level evaluation index i, constructing a judgment matrix
And a weight vector Wi＝{w1,w2,…wT}; wherein T represents the number of next-level evaluation indexes of the previous-level evaluation index i, and J represents the number of protection effect grades;
according to formula Bi＝Wi·RiCalculating a fuzzy evaluation vector B of the upper-level evaluation index ii。
6. The evaluation method according to claim 1, wherein the fuzzy evaluation vector defining the top-level evaluation index is B ═ (B)01,b02,…,b0j,…,b0J)，b0jThe membership degree of the j-th level protection effect of the evaluation index representing the top level;
correspondingly, the determining the level of the DAS protection effect according to the fuzzy evaluation vector of the top-level evaluation index and the absolute difference of the pre-constructed ideal evaluation matrix specifically includes:
for the mth row element of the ideal evaluation matrix, the absolute difference delta between each element in the mth row and the corresponding element in the fuzzy evaluation vector B is calculatedmjWherein j represents the j-th column element in the ideal evaluation matrix and the fuzzy evaluation vector;
calculating the fuzzy score according to the following formulaCorrelation coefficient theta of valence vector B and m row elementmj：
Wherein, DeltamaxRepresents the maximum absolute difference, Δ, between all elements in the ideal evaluation matrix and the corresponding element in the fuzzy evaluation vector BminRepresenting the minimum absolute difference between all elements in the ideal evaluation matrix and the corresponding elements in the fuzzy evaluation vector B, and α is 0.5;
according to the formula
Determining the relevance sigma of the fuzzy evaluation vector B and the mth row element of the ideal evaluation matrixBVm；
And (5) counting the relevance between the fuzzy evaluation vector B and all the protection effect grades, and taking the protection effect grade corresponding to the maximum relevance as the grade of the DAS protection effect.
7. The method of claim 3, wherein if CR > 0.1, the decision matrix is adjusted until a consistency check is passed.
8. An apparatus for evaluating DAS protective effects, comprising:
the system construction module is used for constructing an evaluation index system comprising multi-level evaluation indexes;
the weight calculation module is used for calculating the weight of each next-level evaluation index in the evaluation index system to the previous-level evaluation index;
the membership calculation module is used for dividing the protection effect into a plurality of grades, and calculating the membership of each next-level evaluation index of the previous-level evaluation indexes to the protection effect grade for any previous-level evaluation index;
the fuzzy evaluation vector calculation module is used for obtaining a fuzzy evaluation vector of each upper-level evaluation index according to the weight of each lower-level evaluation index on the upper-level evaluation index and the membership degree of each lower-level evaluation index on the protection effect grade;
the grade determining module is used for determining the grade of the DAS protection effect according to the fuzzy evaluation vector of the top-grade evaluation index and the absolute difference of a pre-constructed ideal evaluation matrix;
the fuzzy evaluation vector is used for representing the membership degree of the corresponding previous-level evaluation index to the protection effect grade, the ideal evaluation matrix is an identity matrix, and the jth row element is used for representing the membership degree of the top-level evaluation index to the jth protection effect in an ideal state.
9. An electronic device, comprising:
at least one processor; and
at least one memory communicatively coupled to the processor, wherein:
the memory stores program instructions executable by the processor to invoke a method of evaluating the effectiveness of DAS safeguards as claimed in any of claims 1 to 7.
10. A non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the method for evaluating DAS protective effects according to any one of claims 1 to 7.
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