CN110458463B - Electric power Internet of things security assessment method based on interval intuitive fuzzy decision - Google Patents

Electric power Internet of things security assessment method based on interval intuitive fuzzy decision Download PDF

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CN110458463B
CN110458463B CN201910753134.3A CN201910753134A CN110458463B CN 110458463 B CN110458463 B CN 110458463B CN 201910753134 A CN201910753134 A CN 201910753134A CN 110458463 B CN110458463 B CN 110458463B
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臧天磊
何正友
向悦萍
杨健维
罗杰
王艳
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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

Electric power Internet of things safety assessment method based on interval intuitive fuzzy decision
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:
Figure BDA0002167884390000021
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 to
Figure BDA0002167884390000031
zk,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,
Figure BDA0002167884390000032
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 evaluation
Figure BDA0002167884390000033
Wherein
Figure BDA0002167884390000034
Is an interval intuitive fuzzy number,
Figure BDA0002167884390000035
and
Figure BDA0002167884390000036
respectively are membership degree and non-membership degree, and satisfy
Figure BDA0002167884390000037
Figure BDA0002167884390000038
Wherein
Figure BDA0002167884390000039
And
Figure BDA00021678843900000310
are respectively as
Figure BDA00021678843900000311
And
Figure BDA00021678843900000312
lower and upper interval limits.
The step 4 is specifically:
interval intuition fuzzy decision matrix given by power Internet of things security assessment expert group
Figure BDA00021678843900000313
Is an interval intuitive fuzzy number; giving the ith to-be-evaluated power Internet of things I based on the matrixiIntegrated interval intuitive fuzzy number
Figure BDA00021678843900000314
Namely, it is
Figure BDA00021678843900000315
i＝1,2,…,m
Wherein
Figure BDA00021678843900000316
And
Figure BDA00021678843900000317
respectively an intuitive fuzzy number of the integrated interval
Figure BDA00021678843900000318
Lower 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 function
Figure BDA00021678843900000319
i is 1,2, …, m, the score function
Figure BDA00021678843900000320
And exact function
Figure BDA00021678843900000321
Respectively as follows:
Figure BDA00021678843900000322
Figure BDA00021678843900000323
score function
Figure BDA00021678843900000324
The larger the value is, the more the integrated interval intuitionistic fuzzy number is
Figure BDA00021678843900000325
The larger the score function of the intuitive fuzzy number of a plurality of integrated sections
Figure BDA00021678843900000326
If the values are equal, the exact functions are compared
Figure BDA00021678843900000327
The value of the one or more of the one,
Figure BDA00021678843900000328
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 interval
Figure BDA00021678843900000329
The size of the network E of the electric power Internet to be evaluatediPerforming safe sorting and synthesizing interval intuitive fuzzy numbers
Figure BDA00021678843900000330
The 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.
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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:
Figure BDA0002167884390000051
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 to
Figure BDA0002167884390000061
zk,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),
Figure BDA0002167884390000062
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 evaluation
Figure BDA0002167884390000063
Wherein
Figure BDA0002167884390000064
Is an interval intuitive fuzzy number,
Figure BDA0002167884390000065
and
Figure BDA0002167884390000066
respectively are membership degree and non-membership degree, and satisfy
Figure BDA0002167884390000067
Figure BDA0002167884390000068
Wherein
Figure BDA0002167884390000069
And with
Figure BDA00021678843900000610
Are respectively as
Figure BDA00021678843900000611
And with
Figure BDA00021678843900000612
Lower 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 group
Figure BDA00021678843900000613
Is an interval intuitive fuzzy number; giving out ith to-be-evaluated power Internet of things I based on matrixiIntegrated interval intuitive fuzzy number
Figure BDA00021678843900000614
Namely, it is
Figure BDA00021678843900000615
i＝1,2,…,m
Wherein
Figure BDA00021678843900000616
And
Figure BDA00021678843900000617
respectively an intuitive fuzzy number of the integrated interval
Figure BDA00021678843900000618
Lower 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 function
Figure BDA00021678843900000619
i is 1,2, …, m, the score function
Figure BDA00021678843900000620
And exact function
Figure BDA00021678843900000621
Respectively as follows:
Figure BDA00021678843900000622
Figure BDA00021678843900000623
score function
Figure BDA00021678843900000624
The larger the value is, the more the integrated interval intuitionistic fuzzy number is
Figure BDA00021678843900000625
The larger the score function is, the more the integral interval is
Figure BDA00021678843900000626
If the values are equal, the exact functions are compared
Figure BDA00021678843900000627
The value of the sum of the values,
Figure BDA00021678843900000628
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 interval
Figure BDA00021678843900000629
The size of the network E of the electric power Internet to be evaluatediSafe sorting is carried out, and interval intuitionistic fuzzy numbers are integrated
Figure BDA0002167884390000071
The 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
Figure BDA0002167884390000072
(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
Figure BDA0002167884390000073
Figure BDA0002167884390000081
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
Figure BDA0002167884390000082
(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
Figure BDA0002167884390000091
(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.
Figure BDA0002167884390000092
Figure BDA0002167884390000093
Figure BDA0002167884390000094
Method for quantizing interval intuitive fuzzy number by using score function and precision function
Figure BDA0002167884390000095
(i-1, 2,3), i.e. a scoring function
Figure BDA0002167884390000096
And function of accuracy
Figure BDA0002167884390000097
Are respectively as
Figure BDA0002167884390000098
Figure BDA0002167884390000099
Figure BDA00021678843900000910
By a scoring function
Figure BDA0002167884390000101
The value (i is 1,2,3) is known, and the safety level of 3 power internet of things to be evaluated is ranked as E1＞E3＞E2And the 1 st construction scheme is adopted, so that the operation safety of the power internet of things is higher.

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:
Figure FDA0002167884380000011
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 to
Figure FDA0002167884380000021
zk,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)；
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),
Figure FDA0002167884380000022
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 evaluation
Figure FDA0002167884380000023
Wherein
Figure FDA0002167884380000024
Is an interval intuitive fuzzy number,
Figure FDA0002167884380000025
and
Figure FDA0002167884380000026
respectively are membership degree and non-membership degree, and satisfy
Figure FDA0002167884380000027
Figure FDA0002167884380000028
Wherein
Figure FDA0002167884380000029
And
Figure FDA00021678843800000210
are respectively as
Figure FDA00021678843800000211
And
Figure FDA00021678843800000212
lower 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
Figure FDA0002167884380000031
Figure FDA0002167884380000032
Is an interval intuitive fuzzy number; giving the ith to-be-evaluated power Internet of things I based on the matrixiIntegrated interval intuitive fuzzy number
Figure FDA0002167884380000033
Namely, it is
Figure FDA0002167884380000034
Wherein
Figure FDA0002167884380000035
And
Figure FDA0002167884380000036
respectively an intuitive fuzzy number of the integrated interval
Figure FDA0002167884380000037
Lower limit and upper limit of the interval of the membership degree and the non-membership degree; wherein
Figure FDA0002167884380000038
And
Figure FDA0002167884380000039
respectively an interval intuitive fuzzy number
Figure FDA00021678843800000310
Lower 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 function
Figure FDA00021678843800000311
I.e. the score function
Figure FDA00021678843800000312
And exact function
Figure FDA00021678843800000313
Respectively as follows:
Figure FDA00021678843800000314
Figure FDA00021678843800000315
score function
Figure FDA00021678843800000316
The larger the value is, the more the integrated interval intuitionistic fuzzy number is
Figure FDA00021678843800000317
The larger the score function of the intuitive fuzzy number of a plurality of integrated sections
Figure FDA00021678843800000318
If the values are equal, the exact functions are compared
Figure FDA00021678843800000319
The value of the one or more of the one,
Figure FDA00021678843800000320
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 interval
Figure FDA00021678843800000321
The size of the network E of the electric power Internet to be evaluatediSafe sorting is carried out, and interval intuitionistic fuzzy numbers are integrated
Figure FDA00021678843800000322
The larger the power internet of things is, the higher the safety level of the power internet of things is.
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