CN110458463B - Electric power Internet of things security assessment method based on interval intuitive fuzzy decision - Google Patents
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Abstract
The invention discloses a safety assessment method for an electric power internet of things based on interval intuitive fuzzy decision, which comprises the following specific steps: firstly, establishing a power internet of things safety evaluation index set from 4 angles of perception safety, network safety, application safety and cloud edge cooperative safety, and collecting each index data to form an evaluation decision matrix; then, forming a power Internet of things safety index weighting expert group, and solving the comprehensive weight given by a plurality of expert groups by adopting a group decision characteristic root method; further, a power Internet of things safety assessment expert group is formed, and the expert group performs interval fuzzy evaluation on index values in the safety assessment decision matrix; and finally, giving a safety evaluation result of the power internet of things by adopting an interval intuitive fuzzy decision method. The safety evaluation index system of the power internet of things is comprehensive, the evaluation method is feasible, planning and construction of the power internet of things are facilitated, and the safety protection level of the power internet of things is improved.
Description
Technical Field
The invention belongs to the technical field of power systems, and particularly relates to a power internet of things safety assessment method based on interval intuitive fuzzy decision.
Background
The power internet of things comprises various links of source-network-load-storage, generation-output-distribution-use and the like of a power energy network, and power equipment, network elements, power utilization equipment and the like are closely connected, so that ubiquitous (any time, any place, any person and any object) efficient communication is realized. In the construction and operation of the power internet of things, one of the key concerns is how to perform security assessment so as to guarantee the security of the information transmission and data application process and avoid the accident threatening the security of the power internet of things system as far as possible. In order to guarantee the safety of the power internet of things, the safety of a sensing layer, a network layer, an application layer and a platform layer needs to be comprehensively considered, and the safety condition of the power internet of things needs to be comprehensively evaluated.
Disclosure of Invention
In view of this, an electric power internet of things security evaluation system is constructed from multiple perspectives such as perception security, network security, application security, cloud-edge collaborative security and the like. The invention provides a safety assessment method for an electric power internet of things based on interval intuition fuzzy decision, which is used for comprehensively assessing the safety condition of the electric power internet of things. The scheme is as follows:
a safety assessment method for an electric power Internet of things based on interval intuitive fuzzy decision includes the following steps:
step 1: constructing a power internet of things safety assessment index set, and collecting each safety assessment index data to form a power internet of things safety assessment decision matrix;
step 2: forming a power Internet of things safety evaluation index empowerment expert group, and solving the comprehensive weight given by the whole expert group by adopting a group decision characteristic root method;
and step 3: forming a power Internet of things safety evaluation expert group, and performing interval fuzzy evaluation on index values in a safety evaluation decision matrix by the expert group;
and 4, step 4: and giving a safety evaluation result of the power Internet of things by adopting an interval intuitive fuzzy decision method.
The safety evaluation indexes of the power internet of things in the step 1 include 4 types, namely perception safety, network safety, application safety and cloud edge cooperative safety, and specifically include the following evaluation indexes:
a. perception of security indicators: the system comprises object privacy safety, intelligent node safety, node information authentication and control capability and anti-attack capability of a wireless sensor network.
b. Network security index: physical environment security, communication network security, software data security, IPv6 application risk, and heterogeneous network identification and integration strength.
c. Application safety indexes are as follows: role recognition efficiency, business safety, platform supporting safety, normal working time of software and hardware, disaster control and recovery capability.
d. Cloud-edge collaborative security indexes: the system comprises cloud-side collaborative computing platform safety, cloud-side collaborative computing monitoring capability, information application safety, data isolation and recovery efficiency, user access control capability and long-term survival time of a supplier.
The value of the safety evaluation index of the power internet of things is determined by a scoring method (the total score is 10), and the higher the index value is, the better the safety performance is.
The method for forming the electric power internet of things security assessment decision matrix in the step 1 comprises the following steps:
assuming that the total number of the to-be-evaluated electric power internet of things is m, the number of safety evaluation indexes is n, and the ith electric power internet of things is IiI is 1,2, …, m, then the power internet of things IiIs set as { yi1,yi2,…,yij,…,yin},j=1,2,…,n,yijRepresenting the value of the jth safety assessment index of the ith power internet of things; then all yijAnd (3) forming a security assessment decision matrix Y:
the step 2 is specifically:
an electric power Internet of things safety evaluation index empowerment expert group consisting of p experts is set, and ideal safety indexes are recordedThe right-assigning expert is E*The security index of each power internet of things is endowed with the same weight as the whole expert group E, and E is (E ═ E-1,E2,…,Ek,…,Ep) K 1,2, …, p, expert EkThe weight vector given to each evaluation index is wk,wkIs an n-order vector, and all experts give a weight forming matrix of w ═ w1,w2,…,wk,…,wp);
According to matrix theory and characteristic root method, ideal safety index empowerment expert E*The given weight, i.e. the overall weight given by the entire expert population, ω ═ ω (ω ═ ω [ ]1,ω2,…,ωj,…,ωn) J ═ 1,2, …, n, determined as follows:
1) let the feature matrix F be wTw;
2) Setting the precision epsilon;
3) assuming that the iteration number k is equal to 0, the intermediate value matrix y is initialized0=[1/n,1/n,…,1/n]TLet the matrix y1=Fy0Then iterate the initial value matrix z1=y1/||y1||2;
4) Let k be k +1, the intermediate value matrix y is iteratedk+1=FzkMatrix of iterative values zk+1=yk+1/||yk+1||2;
5) Order tozk,jAn iterative initial value matrix of the jth safety evaluation index if epsilonz< ε, then zk+1Is the ideal safety index empowerment expert E*Is (theta) is the overall evaluation vector of (theta)1,θ2,…,θj,…,θn);
6) The comprehensive evaluation vector theta is normalized, and the comprehensive weight omega given by the whole expert group is obtained (omega)1,ω2,…,ωj,…,ωn) Wherein, in the process,
the step 3 is specifically:
forming a power Internet of things safety evaluation expert group, and taking the value y of the jth safety evaluation index of the ith power Internet of thingsijI is 1,2, …, m; j 1,2, …, n, the expert group gives an interval intuitive fuzzy evaluationWhereinIs an interval intuitive fuzzy number,andrespectively are membership degree and non-membership degree, and satisfy WhereinAndare respectively asAndlower and upper interval limits.
The step 4 is specifically:
interval intuition fuzzy decision matrix given by power Internet of things security assessment expert groupIs an interval intuitive fuzzy number; giving the ith to-be-evaluated power Internet of things I based on the matrixiIntegrated interval intuitive fuzzy numberNamely, it is
i=1,2,…,m
WhereinAndrespectively an intuitive fuzzy number of the integrated intervalLower limit and upper limit of the interval of the membership degree and the non-membership degree;
method for quantizing intuitive fuzzy number of comprehensive interval by using score function and precision functioni is 1,2, …, m, the score functionAnd exact functionRespectively as follows:
score functionThe larger the value is, the more the integrated interval intuitionistic fuzzy number isThe larger the score function of the intuitive fuzzy number of a plurality of integrated sectionsIf the values are equal, the exact functions are comparedThe value of the one or more of the one,the larger the value is, the larger the corresponding comprehensive interval intuitionistic fuzzy number is; accordingly, the fuzzy number is intuitively recognized according to the comprehensive intervalThe size of the network E of the electric power Internet to be evaluatediPerforming safe sorting and synthesizing interval intuitive fuzzy numbersThe larger the power internet of things is, the higher the safety level of the power internet of things is.
The invention has the beneficial effects that:
the method comprehensively considers factors such as sensing safety, network safety, application safety, cloud-edge cooperative safety and the like, constructs a safety evaluation index set of the power internet of things comprising 20 evaluation indexes, and can systematically and comprehensively reflect the safety level of the power internet of things; the comprehensive weight of the evaluation index is determined by adopting a group decision characteristic root method, the weight opinions given by multiple experts can be effectively integrated, and the reasonability of weighting is realized.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and specific embodiments.
The invention provides a safety assessment method for an electric power internet of things based on interval intuitive fuzzy decision, which comprises the following specific steps as shown in figure 1:
step 1: constructing a safety assessment index set of the power Internet of things, and collecting data of each safety assessment index to form a safety assessment decision matrix of the power Internet of things;
(1) electric power thing networking safety assessment index set
The safety evaluation indexes of the power internet of things comprise 4 types, namely perception safety, network safety, application safety and cloud edge cooperation safety, and specifically comprise the following evaluation indexes:
a. perception of security indicators: the system comprises object privacy safety, intelligent node safety, node information authentication and control capability and anti-attack capability of a wireless sensor network. The object privacy safety index indicates whether object information can be effectively hidden in the power internet of things; the security threats of the intelligent node comprise: the method comprises the following steps that gateway nodes of a wireless sensing network are mastered by an attacker, public nodes are mastered by the attacker, the public nodes are captured by the attacker, DDoS attack from an external network of a power system, physical damage to intelligent nodes and the like are realized; the node information authentication and control capability index indicates that the validity of the node access information authentication in the power internet of things ensures that a legal user accesses and controls a corresponding node.
b. Network security index: physical environment security, communication network security, software data security, IPv6 application risk, and heterogeneous network identification and integration strength. Wherein, the safety index of physical environment refers to the safety in the aspect of electric power thing networking computer lab and office building and supporting facility, equipment, circuit and power consumption, includes: the buildings, equipment or lines are damaged or have faults, the equipment is stolen, information leakage occurs, power utilization interruption occurs and the like; the communication network safety index is used for preventing and protecting hardware problems, software problems and data information in the communication network according to the characteristics of the power internet of things; security threats for software data include: unsafe access between the interior of a power grid enterprise and each department, unreliable safety environment for data interaction and storage of each application system, hidden content danger of offline unstructured data, lack of uniform safety management of terminal peripheral ports and the like; the risk of IPv6 application includes the equipment counterfeiting access network, vulnerability caused by application layer attack, attack in the information transmission process and the like. The heterogeneous network identification and integration strength index represents the capability of the power internet of things in resisting heterogeneous network attack.
c. Application safety indexes are as follows: role recognition efficiency, business safety, platform supporting safety, normal working time of software and hardware, disaster control and recovery capability.
d. Cloud-edge collaborative security indexes: the system comprises cloud-side collaborative computing platform safety, cloud-side collaborative computing monitoring capability, information application safety, data isolation and recovery efficiency, user access control capability and long-term survival time of a supplier.
The value of the safety evaluation index of the power internet of things is determined by a scoring method (the total score is 10), and the higher the index value is, the better the safety performance is.
(2) Form a security assessment decision matrix of the power internet of things
Assuming that the total number of the to-be-evaluated electric power internet of things is m, the number of safety evaluation indexes is n, and the ith electric power internet of things is IiI is 1,2, …, m, then the power internet of things IiIs set as { yi1,yi2,…,yij,…,yin},j=1,2,…,n,yijRepresenting the value of the jth safety assessment index of the ith power internet of things; then all yijAnd (3) forming a security assessment decision matrix Y:
step 2: forming a power Internet of things safety evaluation index empowerment expert group, and solving the comprehensive weight given by the whole expert group by adopting a group decision characteristic root method;
an electric power plant composed of p expertsThe networking safety evaluation index empowerment expert group records the ideal safety index empowerment expert as E*The security index of each power internet of things is endowed with the same weight as the whole expert group E, and E is (E ═ E-1,E2,…,Ek,…,Ep) K 1,2, …, p expert EkThe weight vector given to each evaluation index is wk,wkIs an n-order vector, and all experts give a weight forming matrix of w ═ w1,w2,…,wk,…,wp);
According to matrix theory and characteristic root method, ideal safety index empowerment expert E*The given weight, i.e. the overall weight given by the entire expert population, ω ═ ω (ω ═ ω [ ]1,ω2,…,ωj,…,ωn) J ═ 1,2, …, n, determined as follows:
1) let the feature matrix F be wTw;
2) Setting the precision epsilon;
3) assuming that the iteration number k is equal to 0, the intermediate value matrix y is initialized0=[1/n,1/n,…,1/n]TLet matrix y1=Fy0Then iterate the initial value matrix z1=y1/||y1||2;
4) Let k be k +1, the intermediate value matrix y is iteratedk+1=FzkMatrix of iterative values zk+1=yk+1/||yk+1||2;
5) Order tozk,jAn iterative initial value matrix of the jth safety evaluation index if epsilonz< ε, then zk+1Is the ideal safety index empowerment expert E*Is (theta) is the overall evaluation vector of (theta)1,θ2,…,θj,…,θn);
6) The comprehensive evaluation vector theta is normalized, and the comprehensive weight omega given by the whole expert group is obtained (omega)1,ω2,…,ωj,…,ωn) Wherein, in the step (A),
and step 3: forming a power Internet of things safety evaluation expert group, and performing interval fuzzy evaluation on index values in a safety evaluation decision matrix by the expert group;
forming a power Internet of things safety evaluation expert group, and taking y as the jth safety evaluation index value of the ith power Internet of thingsijI is 1,2, …, m; j 1,2, …, n, the expert group gives an interval intuitive fuzzy evaluationWhereinIs an interval intuitive fuzzy number,andrespectively are membership degree and non-membership degree, and satisfy WhereinAnd withAre respectively asAnd withLower and upper interval limits.
And 4, step 4: and giving a safety evaluation result of the power Internet of things by adopting an interval intuitive fuzzy decision method.
Interval intuition fuzzy decision matrix given by power Internet of things safety assessment expert groupIs an interval intuitive fuzzy number; giving out ith to-be-evaluated power Internet of things I based on matrixiIntegrated interval intuitive fuzzy numberNamely, it is
i=1,2,…,m
WhereinAndrespectively an intuitive fuzzy number of the integrated intervalLower limit and upper limit of the interval of the membership degree and the non-membership degree;
method for quantizing intuitive fuzzy number of comprehensive interval by using score function and precision functioni is 1,2, …, m, the score functionAnd exact functionRespectively as follows:
score functionThe larger the value is, the more the integrated interval intuitionistic fuzzy number isThe larger the score function is, the more the integral interval isIf the values are equal, the exact functions are comparedThe value of the sum of the values,the larger the value is, the larger the corresponding comprehensive interval intuitionistic fuzzy number is; accordingly, the fuzzy number is intuitively recognized according to the comprehensive intervalThe size of the network E of the electric power Internet to be evaluatediSafe sorting is carried out, and interval intuitionistic fuzzy numbers are integratedThe larger the power internet of things is, the higher the safety level of the power internet of things is.
Examples
The method is characterized in that three electric power Internet of things construction schemes to be evaluated are set and are respectively recorded as an electric power Internet of things 1, an electric power Internet of things 2 and an electric power Internet of things 3.
(1) Constructing a safety assessment index set of the power internet of things, and collecting data of each index to form an assessment decision matrix;
and scoring by the power Internet of things safety assessment expert group according to a set standard, and respectively taking the average value of the scores of all the indexes. The obtained data are shown in Table 1.
Table 1 electric power internet of things security evaluation index and evaluation decision matrix element value
(2) Forming a power Internet of things safety index empowerment expert group, and solving the comprehensive weight given by a plurality of expert groups by adopting a group decision characteristic root method;
an electric power internet of things safety index weighting expert group is formed by 3 experts, and index weights and comprehensive weights (obtained by a feature root method) given by the experts are shown in table 2.
TABLE 2 index weights and composite index weights given by each expert in the weighted expert group
Iterative initial value matrix z in process of solving comprehensive weight by characteristic root method1And a matrix of iteration values zk+1The elements in (k ═ 1,2,3,4) are shown in table 3. As can be seen from table 3, when the integrated weight is obtained, it can be converged to a high accuracy in several iterations.
TABLE 3 iterating elements in the initial value matrix and the iteration value matrix
(3) Forming a power Internet of things safety evaluation expert group, and performing interval fuzzy evaluation on index values in a safety evaluation decision matrix by the expert group;
the electric power internet of things safety assessment expert group gives interval intuitive fuzzy assessment to all indexes of 3 electric power internet of things to be assessed, and elements in an interval intuitive fuzzy decision matrix are shown in table 4.
TABLE 4 Interval intuitive fuzzy decision matrix elements given by the Security assessment expert group
(4) And giving a safety evaluation result of the power Internet of things by adopting an interval intuitive fuzzy decision method.
3 to-be-evaluated power Internet of things I based on interval intuitive fuzzy decision matrixiIntegrated interval intuitive fuzzy value of (i ═ 1,2,3), i.e.
Method for quantizing interval intuitive fuzzy number by using score function and precision function(i-1, 2,3), i.e. a scoring functionAnd function of accuracyAre respectively as
Claims (6)
1. A safety assessment method for an electric power Internet of things based on interval intuitive fuzzy decision is characterized by comprising the following steps:
step 1: constructing a power internet of things safety assessment index set, and collecting each safety assessment index data to form a power internet of things safety assessment decision matrix;
step 2: forming a power Internet of things safety evaluation index weighting expert group, and solving the comprehensive weight given by the whole expert group by adopting a group decision characteristic root method;
and step 3: forming a power Internet of things safety evaluation expert group, and performing interval fuzzy evaluation on index values in a safety evaluation decision matrix by the expert group;
and 4, step 4: and giving a safety evaluation result of the power Internet of things by adopting an interval intuitive fuzzy decision method.
2. The electric power internet of things security assessment method based on interval intuitive fuzzy decision-making according to claim 1, wherein the electric power internet of things security assessment index set comprises perception security, network security, application security and cloud-edge cooperative security;
the perceived security indicators include: the method comprises the following steps of object privacy safety, intelligent node safety, node information authentication and control capacity and attack resistance of a wireless sensor network;
the network security indicators include: physical environment security, communication network security, software data security, IPv6 application risk, heterogeneous network identification and integration strength;
the application security indicators include: role recognition efficiency, business safety, platform safety support, normal software and hardware working time, disaster control and recovery capability;
the cloud edge collaborative security indexes include: the method comprises the following steps of cloud-side collaborative computing platform safety, cloud-side collaborative computing monitoring capability, information application safety, data isolation and recovery efficiency, user access control capability and long-term survival time of a supplier;
the value of the safety evaluation index of the power internet of things is determined by a grading method, the total score is 10, and the higher the index value is, the better the safety performance is.
3. The electric power internet of things safety assessment method based on interval intuitive fuzzy decision-making as claimed in claim 1, wherein the method for forming the electric power internet of things safety assessment decision matrix is as follows:
assuming that the total number of the to-be-evaluated electric power internet of things is m, the number of safety evaluation indexes is n, and the ith electric power internet of things is IiI is 1,2, …, m, then the power internet of things IiIs set as { yi1,yi2,…,yij,…,yin},j=1,2,…,n,yijRepresenting the value of the jth safety assessment index of the ith power internet of things; then all yijAnd (3) forming a security assessment decision matrix Y:
4. the electric power internet of things security assessment method based on interval intuitive fuzzy decision-making according to claim 1, wherein the step 2 specifically comprises:
let P experts form electric power thing networking safety assessment indexAnd the empowerment expert group records the ideal safety index empowerment expert as E, the empowerment of the safety index of each power Internet of things is highly consistent with the E of the whole expert group, and E is (E)1,E2,…,Ek,…,Ep) K 1,2, …, p expert EkThe weight vector given to each evaluation index is wk,wkIs an n-order vector, and all experts give a weight forming matrix of w ═ w1,w2,…,wk,…,wp);
According to the matrix theory and the characteristic root method, the ideal safety index is weighted by the weight given by the expert E, namely the comprehensive weight omega given by the whole expert group is (omega)1,ω2,…,ωj,…,ωn) J ═ 1,2, …, n, determined as follows:
1) let the feature matrix F be wTw;
2) Setting the precision epsilon;
3) assuming that the iteration number k is equal to 0, the intermediate value matrix y is initialized0=[1/n,1/n,…,1/n]TLet the matrix y1=Fy0Then iterate the initial value matrix z1=y1/||y1||2;
4) Let k be k +1, the intermediate value matrix y is iteratedk+1=FzkMatrix of iterative values zk+1=yk+1/||yk+1||2;
5) Order tozk,jAn iterative initial value matrix of the jth safety evaluation index if epsilonz< ε, then zk+1I.e. the comprehensive evaluation vector theta (theta) of the ideal safety index empowerment expert E1,θ2,…,θj,…,θn);
5. the electric power internet of things security assessment method based on interval intuitive fuzzy decision-making according to claim 1, wherein the step 3 specifically comprises:
forming a power Internet of things safety evaluation expert group, and taking y as the jth safety evaluation index value of the ith power Internet of thingsijI is 1,2, …, m; j 1,2, …, n, the expert group gives an interval intuitive fuzzy evaluationWhereinIs an interval intuitive fuzzy number,andrespectively are membership degree and non-membership degree, and satisfy WhereinAndare respectively asAndlower and upper interval limits.
6. The electric power internet of things security assessment method based on interval intuitive fuzzy decision-making according to claim 1, wherein the step 4 specifically comprises:
interval intuition fuzzy decision matrix given by power Internet of things safety assessment expert group Is an interval intuitive fuzzy number; giving the ith to-be-evaluated power Internet of things I based on the matrixiIntegrated interval intuitive fuzzy numberNamely, it is
WhereinAndrespectively an intuitive fuzzy number of the integrated intervalLower limit and upper limit of the interval of the membership degree and the non-membership degree; whereinAndrespectively an interval intuitive fuzzy numberLower limit and upper limit of the interval between the membership degree and the non-membership degree;
method for quantizing intuitive fuzzy number of comprehensive interval by using score function and precision functionI.e. the score functionAnd exact functionRespectively as follows:
score functionThe larger the value is, the more the integrated interval intuitionistic fuzzy number isThe larger the score function of the intuitive fuzzy number of a plurality of integrated sectionsIf the values are equal, the exact functions are comparedThe value of the one or more of the one,the larger the value is, the larger the corresponding comprehensive interval intuitionistic fuzzy number is; accordingly, the fuzzy number is intuitively recognized according to the comprehensive intervalThe size of the network E of the electric power Internet to be evaluatediSafe sorting is carried out, and interval intuitionistic fuzzy numbers are integratedThe larger the power internet of things is, the higher the safety level of the power internet of things is.
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