CN112437407A - Method and system for calculating initialized safety state of power internet of things wireless terminal equipment based on mixed information entropy - Google Patents
Method and system for calculating initialized safety state of power internet of things wireless terminal equipment based on mixed information entropy Download PDFInfo
- Publication number
- CN112437407A CN112437407A CN202010991544.4A CN202010991544A CN112437407A CN 112437407 A CN112437407 A CN 112437407A CN 202010991544 A CN202010991544 A CN 202010991544A CN 112437407 A CN112437407 A CN 112437407A
- Authority
- CN
- China
- Prior art keywords
- trust
- value
- wireless communication
- communication terminal
- determining
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 50
- 238000004891 communication Methods 0.000 claims abstract description 92
- 238000009826 distribution Methods 0.000 claims abstract description 89
- 238000011156 evaluation Methods 0.000 claims abstract description 33
- 230000002452 interceptive effect Effects 0.000 claims abstract description 12
- 230000003993 interaction Effects 0.000 claims description 20
- 230000003247 decreasing effect Effects 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 abstract description 6
- 230000006870 function Effects 0.000 description 37
- 102100038522 Fascin-2 Human genes 0.000 description 16
- 101001030534 Homo sapiens Fascin-2 Proteins 0.000 description 16
- 238000010586 diagram Methods 0.000 description 15
- 238000004590 computer program Methods 0.000 description 7
- 230000005611 electricity Effects 0.000 description 5
- 238000012986 modification Methods 0.000 description 5
- 230000004048 modification Effects 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 230000008859 change Effects 0.000 description 4
- 238000003860 storage Methods 0.000 description 4
- 230000006399 behavior Effects 0.000 description 3
- 238000004422 calculation algorithm Methods 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 3
- 238000012937 correction Methods 0.000 description 2
- 238000005315 distribution function Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000013210 evaluation model Methods 0.000 description 1
- 238000012854 evaluation process Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y30/00—IoT infrastructure
- G16Y30/10—Security thereof
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/06—Testing, supervising or monitoring using simulated traffic
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention discloses an initial security state calculation method and system of electric power internet of things wireless terminal equipment based on mixed information entropy, and belongs to the technical field of electric power wireless communication terminals. The method comprises the following steps: determining a direct total trust value of the trust of the electric wireless communication terminal equipment; determining an indirect total trust value trusted by the electric wireless communication terminal equipment; the method comprises the steps of self-adaptively distributing weights of a direct total trust value and an indirect total trust value, determining a weight distribution value, correcting the weight distribution value according to an interactive information utility value of the electric power wireless communication terminal, and obtaining a distribution value of a corrected weight; and performing secondary weight distribution on the direct total trust value and the indirect total trust value according to the corrected weight distribution value, and determining the equipment trust of the electric wireless communication terminal. Aiming at the trust problem of the power wireless private network communication terminal, the invention firstly determines a direct trust value, introduces an indirect trust value to make up the problem of inaccurate direct trust judgment, and improves the trust judgment accuracy through the comprehensive evaluation of the direct trust value and the indirect trust value.
Description
Technical Field
The invention relates to the technical field of power wireless communication terminals, in particular to a method and a system for computing an initialization safety state of power internet of things wireless terminal equipment based on mixed information entropy.
Background
The power internet of things is an important driving part in the energy internet construction process, and the power internet of things is an advanced modern communication information technology such as big data, cloud computing, internet of things, mobile communication and the like, so that interconnection and intercommunication and man-machine interaction of various links such as 'sending, outputting, changing, matching, using and scheduling' of a power system are realized. A large number of terminal devices exist in the power internet of things, have functions of data acquisition, transmission, processing, storage and the like, are numerous and complex in variety, and even do not belong to the same subsystem sometimes. With the continuous development of the power internet of things, the security threat faced by the terminal equipment is increased day by day, and under certain conditions, a forged terminal or a damaged terminal can be converted into a legal terminal to invade the system through identity disguising and capturing a secret key, so that the usability and integrity of the system are damaged, and huge damage is brought to the power system.
In the aspect of network security of the Internet of things, internal attacks of the Internet of things are far more harmful than external attacks. Internal attacks are initiated by malicious or denial of service terminals in the network. In recent years, trust management is considered as one of effective protection mechanisms for ensuring network security, and is an effective way to defend against internal attacks. It evaluates the trust value of the terminal based on its historical behavior, and thus estimates its trustworthiness in performing a particular task. Although preliminary studies have been conducted, some disadvantages still exist, for example, researchers improve the accuracy of trust evaluation by improving trust management based on beta distribution and binomial distribution. However, both of them adopt subjective distribution trust factor, which can lead to inaccurate trust evaluation.
Disclosure of Invention
In order to solve the above problem, the present invention provides a method for calculating an initialized security state of an electric power internet of things wireless terminal device based on a mixed information entropy, which includes:
obtaining trust and index data of the electric wireless communication terminal, fitting a trust function according to an index distribution function, and determining a direct total trust value of the trust of the electric wireless communication terminal equipment;
collecting transaction record data of the electric wireless communication terminal and the public neighbor terminal, and determining an indirect total trust value trusted by the electric wireless communication terminal equipment according to the transaction record data;
the method comprises the steps of self-adaptively distributing weights of a direct total trust value and an indirect total trust value, determining a weight distribution value, correcting the weight distribution value according to an interactive information utility value of the electric power wireless communication terminal, and obtaining a distribution value of a corrected weight;
and performing secondary weight distribution on the direct total trust value and the indirect total trust value according to the corrected weight distribution value, and determining the equipment trust of the electric wireless communication terminal.
Optionally, determining a direct total trust value trusted by the power wireless communication terminal device includes:
the method comprises the steps of obtaining trust distribution and index distribution data in trust and index data of the electric power wireless communication terminal, fitting the trust distribution and index distribution data to obtain a trust degree and credibility model, and determining a cooperation probability function model between the terminals according to the trust degree and credibility model;
determining a credibility and credibility model of a credibility system node based on probability distribution according to a cooperative probability function model between terminals, and establishing a credibility and credibility evaluation system model according to the credibility model and the credibility model based on probability distribution;
and determining a direct total trust value of the trust of the electric wireless communication terminal equipment according to the trust and reputation evaluation system model.
Optionally, the transaction record data includes successful transaction record data and failed transaction record data.
Optionally, the interaction data between the terminals of the cooperative probability function model between the terminals is maintained/+ m times.
Optionally, the function in the cooperative probability function model between the terminals is a monotonically decreasing function.
The invention also provides a system for calculating the initialized safe state of the electric power internet of things wireless terminal equipment based on the mixed information entropy, which comprises the following steps:
the direct trust value acquisition module is used for acquiring trust and index data of the electric wireless communication terminal and determining a direct total trust value trusted by the electric wireless communication terminal equipment according to the trust and index data;
the indirect trust value acquisition module is used for acquiring transaction record data of the electric wireless communication terminal and the public neighbor terminal and determining an indirect total trust value trusted by the electric wireless communication terminal equipment according to the transaction record data;
the weight distribution module is used for adaptively distributing weights of the direct total trust value and the indirect total trust value, determining a weight distribution value, and correcting the weight distribution value according to the interactive information utility value of the power wireless communication terminal to obtain a distribution value of corrected weights;
and the equipment trust acquisition module is used for performing secondary weight distribution on the direct total trust value and the indirect total trust value according to the corrected weight distribution value to determine the equipment trust of the electric wireless communication terminal.
Optionally, determining a direct total trust value trusted by the power wireless communication terminal device includes:
the method comprises the steps of obtaining trust distribution and index distribution data in trust and index data of the electric power wireless communication terminal, fitting the trust distribution and index distribution data to obtain a trust degree and credibility model, and determining a cooperation probability function model between the terminals according to the trust degree and credibility model;
determining a credibility and credibility model of a credibility system node based on probability distribution according to a cooperative probability function model between terminals, and establishing a credibility and credibility evaluation system model according to the credibility model and the credibility model based on probability distribution;
and determining a direct total trust value of the trust of the electric wireless communication terminal equipment according to the trust and reputation evaluation system model.
Optionally, the transaction record data includes successful transaction record data and failed transaction record data.
Optionally, the interaction data between the terminals of the cooperative probability function model between the terminals is maintained/+ m times.
Optionally, the function in the cooperative probability function model between the terminals is a monotonically decreasing function.
Aiming at the trust problem of the power wireless private network communication terminal, the invention firstly determines a direct trust value, introduces an indirect trust value to make up the problem of inaccurate direct trust judgment, and improves the trust judgment accuracy through the comprehensive evaluation of the direct trust value and the indirect trust value.
Drawings
FIG. 1 is a flowchart of an initialization safety state calculation method of an electric power internet of things wireless terminal device based on mixed information entropy according to the present invention;
FIG. 2 is a diagram of a wireless private network telecommunication architecture of an electrical information collection system according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating indirect trust establishment paths for a terminal according to an embodiment of the present invention;
FIG. 4 is a diagram of terminal trust evaluation under selective forwarding attack in an embodiment of the present invention;
FIG. 5 is a diagram of terminal trust evaluation under switch attack in the embodiment of the present invention;
FIG. 6 is a diagram illustrating a terminal trust evaluation under assassassassault by defamation according to an embodiment of the present invention;
FIG. 7 is a diagram illustrating a terminal trust evaluation under assassassassault by defamation according to an embodiment of the present invention;
fig. 8 is a structural diagram of an initialization safety state calculation system of an electric power internet of things wireless terminal device based on mixed information entropy according to the present invention.
Detailed Description
The exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the embodiments described herein, which are provided for complete and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention. In the drawings, the same units/elements are denoted by the same reference numerals.
Unless otherwise defined, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Further, it will be understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
The invention provides a method for calculating an initialized safety state of electric power internet of things wireless terminal equipment based on mixed information entropy, which comprises the following steps of:
obtaining trust and index data of the electric wireless communication terminal, and determining a direct total trust value of trust of the electric wireless communication terminal equipment according to the trust and index data;
collecting transaction record data of the electric wireless communication terminal and the public neighbor terminal, and determining an indirect total trust value trusted by the electric wireless communication terminal equipment according to the transaction record data;
the method comprises the steps of self-adaptively distributing weights of a direct total trust value and an indirect total trust value, determining a weight distribution value, correcting the weight distribution value according to an interactive information utility value of the electric power wireless communication terminal, and obtaining a distribution value of a corrected weight;
and performing secondary weight distribution on the direct total trust value and the indirect total trust value according to the corrected weight distribution value, and determining the equipment trust of the electric wireless communication terminal.
Wherein, the direct total trust value of the trust of the electric wireless communication terminal equipment is determined, which comprises the following steps:
the method comprises the steps of obtaining trust distribution and index distribution data in trust and index data of the electric power wireless communication terminal, fitting the trust distribution and index distribution data to obtain a trust degree and credibility model, and determining a cooperation probability function model between the terminals according to the trust degree and credibility model;
determining a credibility and credibility model of a credibility system node based on probability distribution according to a cooperative probability function model between terminals, and establishing a credibility and credibility evaluation system model according to the credibility model and the credibility model based on probability distribution;
and determining a direct total trust value of the trust of the electric wireless communication terminal equipment according to the trust and reputation evaluation system model.
The transaction record data comprises successful transaction record data and failed transaction record data.
And the interactive data between the terminals of the cooperative probability function model between the terminals is kept for l + m times.
The function in the cooperative probability function model between the terminals is a monotone decreasing function.
The invention is further illustrated by the following examples:
the method comprises the steps of obtaining trust and index data of the electric wireless communication terminal, and determining a direct total trust value of trust of electric wireless communication terminal equipment according to the trust and index data, wherein the direct total trust value comprises the following steps:
firstly, a power wireless communication terminal trust model is established, and the architecture of the wireless communication terminal is as shown in fig. 2, that is, a cooperation probability function model between terminals includes:
fitting according to the trust distribution and the exponential distribution of the power wireless communication terminal to obtain an expression of the trust degree and the credibility of the terminal, setting the interaction between the terminals to be kept for (l + m) times, and obtaining a cooperative probability function modeling between the terminals, wherein the model is as follows:
according to the above-mentioned cooperation probability modeling between the terminals, it represents the reputation R of the terminal j held by the terminal iijWhere,/represents the number of successful interactions, and m represents the number of failed interactions, the formula is as follows:
f (p) is a probability distribution function of the reputation p, the maximum probability of the reputation p being represented by the maximum value of the function, which is defined as the trust value of the terminal, where f' (p benefits the derivative of f (p), TijRepresenting a trust value for terminal i to hold terminal jThe formula is as follows:
it turns out that trust still converges no matter how the number of malicious terminals increases, the formula is as follows:
the trust function is bounded, and T' ij is less than 0 for verifying monotonicity of the function, which indicates that the function is strictly monotonously decreased, and the trust function still converges no matter how the number of malicious terminals increases according to the theorem of monotonous convergence.
Secondly, establishing a trust and reputation evaluation system model, comprising:
the expression of the terminal credibility and the credibility based on the exponential distribution is obtained through the electric power wireless communication terminal trust model, and then a trust and credibility system is established to realize trust evaluation, and the establishment of the electric power wireless communication terminal direct trust evaluation model comprises the following steps:
direct trust calculation, the formula is as follows:
wherein D isijIndicates terminal j to terminal ji direct trust rating value.
Dividing N times of terminal interaction data records recorded by a sliding window of a trust calculation formula into N time slots, numbering each time slot in sequence, and introducing a forgetting factor ut to measure the influence degree of malicious behaviors
And calculating the successful interaction number at the end of the time slot, wherein the formula is as follows:
the number of failed interactions, the formula is as follows:
and further obtaining an updated trust value, wherein the formula is as follows:
direct trust determination, let H (D)ij) Is the entropy of the direct observation, thr is the threshold of uncertainty, when thr ≦ H (D)ij) When the value is less than or equal to 1, the terminal evaluation needs more related information, indirect trust is introduced, and when H (D) is usedij) < thr, the total trust of terminal j can simply be set to the direct trust value, i.e. the total trust OTij＝Dij。
Collecting transaction record data of the electric wireless communication terminal and the public neighbor terminal, determining an indirect total trust value of trust of the electric wireless communication terminal device according to the transaction record data, and establishing an indirect trust link as shown in fig. 3 specifically as follows:
let the successful interaction records observed by the public neighbor terminals as follows:
the failure interaction observed by the public neighbor terminal is recorded as follows:
the recommendations provided by the common neighbor terminal k are as follows:
the trust level of the terminal i for the recommender k is expressed as:
setting r intermediate terminals, and marking the trust value held by the terminal i as Ti1、…、Ti(r-1)、Tir。
If T isikAnd x, the suggestion of the terminal k is used, otherwise, the suggestion is ignored.
Where x (0 ≦ x ≦ 1) is a custom threshold, k ≦ 1, 2 … r.
Weights are assigned according to the recommender's confidence level, as follows:
the indirect trust is then:
the method comprises the steps of self-adaptively distributing weights of a direct total trust value and an indirect total trust value, determining a weight distribution value, correcting the weight distribution value according to an interactive information utility value of the electric power wireless communication terminal, and obtaining a distribution value of a corrected weight;
in order to avoid subjective direct weight distribution, the weight self-adaptive distribution of direct trust and indirect trust is carried out on a terminal trust value based on the information entropy, and the utility value of interactive information provided by the terminal is utilized to realize the correction of the weight distribution value, the specific steps are as follows:
computing a direct trust information entropy value H (D)ij)＝-Dijlog2Dij-(1-Dij)log2(1-Dij)。
Computing an indirect trust information entropy value H (ID)ij)＝-IDijlog2IDij-(1-IDij)log2(1-IDij)。
Weighting direct trust
Weighting indirect trust
The aggregate trust is computed according to a direct trust decision method, as follows:
wherein, OTijIndicating terminal aggregate trust.
And performing secondary weight distribution on the direct total trust value and the indirect total trust value according to the corrected weight distribution value, and determining the equipment trust of the electric wireless communication terminal.
An internal attack scenario of the power wireless communication private network is set as follows, and the explanation is made by combining the attack scenario:
Scene 2 on-off attack scene setting: and setting the interaction periods of the first 20 terminals to be good in performance so as to establish good credit, introducing a small number of malicious terminals in the 20 th period, simulating switch attack, and removing attack behaviors after the 40 th period.
Scene 3 assassassassault scene setting: and setting the terminal j as an unreliable terminal, wherein one of the neighbor terminals between the terminal i and the terminal j is the unreliable terminal, and the rest neighbor terminals are reliable terminals.
Scene 4 collusion attack scene setting: under collusion attack, the malicious terminal can serve as a normal terminal to continue working, the terminal j is set to be unreliable and have unreliable neighbor terminals, and meanwhile, the malicious terminals are combined with respective interaction times.
The terminal equipment of the power internet of things is easily subjected to various security threats such as identity disguise, information stealing, data tampering and the like, a traditional security method cannot resist network internal attack from a damaged terminal, and a trust evaluation system is an effective mechanism for protecting the terminal of the power internet of things from the internal attack.
The present invention is implemented in view of the above-mentioned scenario, which includes 100 interactive communication terminals, including an intelligent electric meter, a charging pile metering device, a pole switch controller, and the like, distributed in a power supply area of 500 × 500m 2. Assuming that the communication capability of each terminal is the same, the communication radius is 50m, and the size of each data packet is 500 bits. In order to ensure the simplicity of network control, the number of neighbors of each terminal is set to be 2 or 3 in the logical connection.
The invention simulates the trust evaluation under different initial trust conditions by using the (l, m) set values of four different scenes, and compares the trust evaluation with the RFSN algorithm based on binomial trust management BTMS and Beta trust management.
As shown in fig. 4, the method of the present invention, BTMS, and RFSN are used to evaluate the trust of the terminal in scenario 1.
The solid line shows that the reliable terminal trust value is gradually improved along with the change of the acquisition period, and the dotted line shows that the malicious terminal trust value is gradually reduced along with the change of the acquisition period, as can be seen from fig. 4, the method and other two methods can distinguish the reliable terminal from the malicious terminal, but the convergence speed of the method is higher, and in the 50 th period, the reliable terminal trust value of the method is 0.9719, the BTMS reliable terminal trust value is 0.9516, and the RFSN reliable terminal trust value is 0.9276;
meanwhile, the method of the invention evaluates the trust value of the malicious terminal to be 0.027, the trust value of the BTMS malicious terminal to be 0.037 and the trust value of the RFSN reliable terminal to be 0.075.
The trust evaluation precision of the algorithm of the invention is improved by 2.13 percent and 4.78 percent respectively compared with BTMS and RFSN on the trust evaluation precision of the reliable terminal; the trust evaluation precision of the malicious terminal is respectively improved by 27.03% and 64.00% compared with that of BTMS and RFSN.
As shown in fig. 5, the situation of the change of the trust value of the switch attack resistance by the method of the present invention, BTMS, and RFSN in scene 2 is shown.
As can be seen from FIG. 5, the trust values of the three methods are all significantly reduced when the switch attack occurs, and slowly rise after the switch attack is finished, but the rate of the decrease of the trust value of the method is much higher than that of RFSN and BTMS, which indicates that the terminal can rapidly lose trust in a short time by only a small amount of bad actions, and indicates that the algorithm can more sensitively detect the malicious attack, and in the 40 th cycle, the terminal trust value of the method is 0.1099, the terminal trust value of BTMS is 0.2698, and the terminal trust value of RFSN is 0.3069.
As shown in fig. 6, the situation that the attack trust value change initiated by the unreliable terminal is resisted by the three methods of the invention, BTMS and RFSN in scene 3 is shown.
As can be seen from fig. 6, when an attack is initiated by an unreliable terminal, the terminal trust values of the three methods are gradually reduced, but the rate of decrease of the trust value of the method of the present invention is faster than that of RFSN and BTMS, which indicates that the method of the present invention has better response performance when resisting the attack initiated by the unreliable terminal, and in the 50 th cycle, the malicious terminal trust value of the method of the present invention is 0.1938, the malicious terminal trust value of BTMS is 0.0880, and the malicious terminal trust value of RFSN is 0.0765.
As shown in fig. 7, the situation that the trust value changes in the collusion attack resistance method, BTMS, and RFSN of the present invention in scene 4 is shown.
As can be seen from fig. 7, the terminal trust value of the method of the present invention is gradually reduced when collusion attack occurs, but the terminal trust values of RFSN and BTMS are gradually increased along with the occurrence of collusion attack. This shows that the method of the present invention can effectively resist collusion attack, while the performance of RFSN and BTMS for resisting collusion attack is poor. In the 30 th period, the trust value of the malicious terminal of the method is 0.2535, the trust value of the malicious terminal of the BTMS is 0.8267, and the trust value of the malicious terminal of the RFSN is 08484.
The power wireless private network communication system composed of the electricity consumption information acquisition terminal equipment, the 230 communication terminal, the communication base station, the core network and the service master station is taken as an example.
A large number of remote communication terminals exist in the electricity utilization information collection wireless communication private network, and the large number of terminals are widely deployed in a low-trust environment and are vulnerable to assarage, switching, defamation, denial of service and the like initiated by malicious terminals or denial of service terminals in the network. In the trust evaluation process, the method is applied to carry out trust evaluation on the remote communication terminal in the electricity consumption information acquisition wireless communication system, and mainly comprises the steps of determining the successful interaction times between the terminals according to the communication time and the data volume between the remote terminals, immediately judging the direct trust of the terminals according to the interaction information between the terminals, introducing the indirect observation entropy of the terminals when the observation entropy of the direct trust value is larger than the set uncertain entropy, realizing the indirect trust evaluation on the target terminal by introducing a neighbor terminal evaluation mechanism, finally carrying out entropy calculation on the direct trust and the indirect trust, and realizing the correction of the weight distribution value by using the utility value of the interaction information provided by the terminals so as to obtain the aggregate trust value of the electricity consumption information acquisition remote communication terminals. In the trust system verification, four attack modes of selective attack, on-off attack, slur attack and collusion attack are carried out on a 230 communication terminal in the electricity utilization information acquisition wireless communication remote terminal equipment.
The invention further provides an initialization safety state computing system 200 of an electric power internet of things wireless terminal device based on mixed information entropy, as shown in fig. 8, including:
the direct trust value acquisition module 201 is used for acquiring trust and index data of the electric wireless communication terminal and determining a direct total trust value trusted by the electric wireless communication terminal equipment according to the trust and index data;
the indirect trust value acquisition module 202 is used for acquiring transaction record data of the electric wireless communication terminal and the public neighbor terminal, and determining an indirect total trust value trusted by the electric wireless communication terminal equipment according to the transaction record data;
the weight distribution module 203 is used for adaptively distributing the weights of the direct total trust value and the indirect total trust value, determining a weight distribution value, and correcting the weight distribution value according to the utility value of the interactive information of the power wireless communication terminal to obtain a distribution value of the corrected weight;
and the device trust obtaining module 203 performs secondary weight distribution on the direct total trust value and the indirect total trust value according to the corrected weight distribution value, and determines the device trust of the electric wireless communication terminal.
Wherein, the direct total trust value of the trust of the electric wireless communication terminal equipment is determined, which comprises the following steps:
the method comprises the steps of obtaining trust distribution and index distribution data in trust and index data of the electric power wireless communication terminal, fitting the trust distribution and index distribution data to obtain a trust degree and credibility model, and determining a cooperation probability function model between the terminals according to the trust degree and credibility model;
determining a credibility and credibility model of a credibility system node based on probability distribution according to a cooperative probability function model between terminals, and establishing a credibility and credibility evaluation system model according to the credibility model and the credibility model based on probability distribution;
and determining a direct total trust value of the trust of the electric wireless communication terminal equipment according to the trust and reputation evaluation system model.
The transaction record data includes successful transaction record data and failed transaction record data.
And (3) keeping the interactive data between the terminals of the cooperative probability function model between the terminals for l + m times.
The function in the cooperative probability function model between the terminals is a monotonically decreasing function.
Aiming at the trust problem of the power wireless private network communication terminal, the invention firstly determines a direct trust value, introduces an indirect trust value to make up the problem of inaccurate direct trust judgment, and improves the trust judgment accuracy through the comprehensive evaluation of the direct trust value and the indirect trust value.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The scheme in the embodiment of the application can be implemented by adopting various computer languages, such as object-oriented programming language Java and transliterated scripting language JavaScript.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (10)
1. A method for evaluating trust of a power wireless communication terminal device, the method comprising:
obtaining trust and index data of the electric wireless communication terminal, and determining a direct total trust value of trust of the electric wireless communication terminal equipment according to the trust and index data;
collecting transaction record data of the electric wireless communication terminal and the public neighbor terminal, and determining an indirect total trust value trusted by the electric wireless communication terminal equipment according to the transaction record data;
the method comprises the steps of self-adaptively distributing weights of a direct total trust value and an indirect total trust value, determining a weight distribution value, correcting the weight distribution value according to an interactive information utility value of the electric power wireless communication terminal, and obtaining a distribution value of a corrected weight;
and performing secondary weight distribution on the direct total trust value and the indirect total trust value according to the corrected weight distribution value, and determining the equipment trust of the electric wireless communication terminal.
2. The method of claim 1, the determining a direct overall trust value trusted by the power wireless communication terminal device, comprising:
the method comprises the steps of obtaining trust distribution and index distribution data in trust and index data of the electric power wireless communication terminal, fitting the trust distribution and index distribution data to obtain a trust degree and credibility model, and determining a cooperation probability function model between the terminals according to the trust degree and credibility model;
determining a credibility and credibility model of a credibility system node based on probability distribution according to a cooperative probability function model between terminals, and establishing a credibility and credibility evaluation system model according to the credibility model and the credibility model based on probability distribution;
and determining a direct total trust value of the trust of the electric wireless communication terminal equipment according to the trust and reputation evaluation system model.
3. The method of claim 1, the transaction record data comprising successful transaction record data and failed transaction record data.
4. The method of claim 2, wherein the data of interaction between terminals of the inter-terminal cooperation probability function model is maintained/+ m times.
5. The method of claim 2, wherein the function in the model of the cooperative probability function between the terminals is a monotonically decreasing function.
6. A system for evaluating trust of a power wireless communication terminal device, the system comprising:
the direct trust value acquisition module is used for acquiring trust and index data of the electric wireless communication terminal and determining a direct total trust value trusted by the electric wireless communication terminal equipment according to the trust and index data;
the indirect trust value acquisition module is used for acquiring transaction record data of the electric wireless communication terminal and the public neighbor terminal and determining an indirect total trust value trusted by the electric wireless communication terminal equipment according to the transaction record data;
the weight distribution module is used for adaptively distributing weights of the direct total trust value and the indirect total trust value, determining a weight distribution value, and correcting the weight distribution value according to the interactive information utility value of the power wireless communication terminal to obtain a distribution value of corrected weights;
and the equipment trust acquisition module is used for performing secondary weight distribution on the direct total trust value and the indirect total trust value according to the corrected weight distribution value to determine the equipment trust of the electric wireless communication terminal.
7. The system of claim 6, said determining a direct overall trust value trusted by the power wireless communication terminal device comprising:
the method comprises the steps of obtaining trust distribution and index distribution data in trust and index data of the electric power wireless communication terminal, fitting the trust distribution and index distribution data to obtain a trust degree and credibility model, and determining a cooperation probability function model between the terminals according to the trust degree and credibility model;
determining a credibility and credibility model of a credibility system node based on probability distribution according to a cooperative probability function model between terminals, and establishing a credibility and credibility evaluation system model according to the credibility model and the credibility model based on probability distribution;
and determining a direct total trust value of the trust of the electric wireless communication terminal equipment according to the trust and reputation evaluation system model.
8. The system of claim 6, the transaction record data comprising successful transaction record data and failed transaction record data.
9. The system of claim 7, wherein the data of the interaction between the terminals of the inter-terminal cooperation probability function model is maintained for I + m times.
10. The system of claim 7, wherein the function in the model of the cooperative probability function between the terminals is a monotonically decreasing function.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010991544.4A CN112437407A (en) | 2020-09-18 | 2020-09-18 | Method and system for calculating initialized safety state of power internet of things wireless terminal equipment based on mixed information entropy |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010991544.4A CN112437407A (en) | 2020-09-18 | 2020-09-18 | Method and system for calculating initialized safety state of power internet of things wireless terminal equipment based on mixed information entropy |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112437407A true CN112437407A (en) | 2021-03-02 |
Family
ID=74690680
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010991544.4A Pending CN112437407A (en) | 2020-09-18 | 2020-09-18 | Method and system for calculating initialized safety state of power internet of things wireless terminal equipment based on mixed information entropy |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112437407A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114302400A (en) * | 2021-10-25 | 2022-04-08 | 国网天津市电力公司 | Electric power 5G wireless private network communication terminal trust evaluation method based on information entropy |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101835158A (en) * | 2010-04-12 | 2010-09-15 | 北京航空航天大学 | Sensor network trust evaluation method based on node behaviors and D-S evidence theory |
| CN102045707A (en) * | 2010-12-28 | 2011-05-04 | 华中科技大学 | Trust construction method for accelerating trust convergence |
| CN102333307A (en) * | 2011-09-28 | 2012-01-25 | 北京航空航天大学 | Wireless sensor network (WSN) trust evaluation method based on subjective belief |
| US20130173616A1 (en) * | 2011-07-08 | 2013-07-04 | Georgia Tech Research Corporation | Systems and methods for providing reputation management |
| CN103297956A (en) * | 2013-05-06 | 2013-09-11 | 北京航空航天大学 | Dynamic lightweight class trust evaluation method based on Bayesian theory and entropy theory |
| CN104836801A (en) * | 2015-04-22 | 2015-08-12 | 上海物联网有限公司 | Binomial-based wireless sensor network trust management method |
| CN107750053A (en) * | 2017-05-25 | 2018-03-02 | 天津大学 | Based on multifactor wireless sensor network dynamic trust evaluation system and method |
-
2020
- 2020-09-18 CN CN202010991544.4A patent/CN112437407A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101835158A (en) * | 2010-04-12 | 2010-09-15 | 北京航空航天大学 | Sensor network trust evaluation method based on node behaviors and D-S evidence theory |
| CN102045707A (en) * | 2010-12-28 | 2011-05-04 | 华中科技大学 | Trust construction method for accelerating trust convergence |
| US20130173616A1 (en) * | 2011-07-08 | 2013-07-04 | Georgia Tech Research Corporation | Systems and methods for providing reputation management |
| CN102333307A (en) * | 2011-09-28 | 2012-01-25 | 北京航空航天大学 | Wireless sensor network (WSN) trust evaluation method based on subjective belief |
| CN103297956A (en) * | 2013-05-06 | 2013-09-11 | 北京航空航天大学 | Dynamic lightweight class trust evaluation method based on Bayesian theory and entropy theory |
| CN104836801A (en) * | 2015-04-22 | 2015-08-12 | 上海物联网有限公司 | Binomial-based wireless sensor network trust management method |
| CN107750053A (en) * | 2017-05-25 | 2018-03-02 | 天津大学 | Based on multifactor wireless sensor network dynamic trust evaluation system and method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114302400A (en) * | 2021-10-25 | 2022-04-08 | 国网天津市电力公司 | Electric power 5G wireless private network communication terminal trust evaluation method based on information entropy |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Liang et al. | A secure fabric blockchain-based data transmission technique for industrial Internet-of-Things | |
| CN103152345A (en) | Network safety optimum attacking and defending decision method for attacking and defending game | |
| CN112633649A (en) | Power grid multi-attribute important node evaluation and planning method | |
| WO2024051822A1 (en) | Multi-terminal collaborative dynamic security analysis method and system for distributed power supply | |
| CN112688315A (en) | Attack and defense system and method based on electric vehicle power distribution network information physical system | |
| CN103747003A (en) | Peer-to-peer botnet core node detection method and detection device | |
| CN112437407A (en) | Method and system for calculating initialized safety state of power internet of things wireless terminal equipment based on mixed information entropy | |
| CN113132398A (en) | Array honeypot system defense strategy prediction method based on Q learning | |
| Li | Network Intrusion Detection Algorithm and Simulation of Complex System in Internet Environment | |
| CN115208604B (en) | AMI network intrusion detection method, device and medium | |
| Li et al. | A hybrid trust management framework for wireless sensor and actuator networks in cyber-physical systems | |
| CN115953044A (en) | Power grid state stability evaluation method based on federal learning and block chain technology | |
| Guan et al. | A Bayesian Improved Defense Model for Deceptive Attack in Honeypot-Enabled Networks | |
| Li et al. | A security defense model for ubiquitous electric internet of things based on game theory | |
| Qian et al. | Based on random game Petri net model CPS risk assessment and defense decision of distribution network | |
| Sridharan et al. | Game-theoretic approach to malicious controller detection in software defined networks | |
| CN113806800A (en) | Privacy protection method and system for improving communication efficiency and reasonably distributing rewards | |
| Yu | Fast Detection of Advanced Persistent Threats for Smart Grids: A Deep Reinforcement Learning Approach | |
| Li et al. | Research on risk prevention and control strategy of power grid CPS system based on intrusion tolerance | |
| CN107995204A (en) | Hadoop framework method for evaluating trust based on Bayes models | |
| CN114124784B (en) | Intelligent routing decision protection method and system based on vertical federation | |
| CN112819300B (en) | Power distribution network risk assessment method based on random game network under network attack | |
| CN114302400A (en) | Electric power 5G wireless private network communication terminal trust evaluation method based on information entropy | |
| CN117556475A (en) | Virtual power plant-oriented distributed multi-party trusted joint learning method | |
| CN112819300A (en) | Power distribution network risk assessment method based on random game network under network attack |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |