A method and system for calculating the initialization security state of a wireless terminal device of the power Internet of Things based on hybrid information entropy

Abstract

The present invention discloses a method and system for calculating the initialization security state of a wireless terminal device of the electric power Internet of Things based on hybrid information entropy, and belongs to the technical field of electric power wireless communication terminals. The method of the present invention includes: determining the direct total trust value of the electric power wireless communication terminal device; determining the indirect total trust value of the electric power wireless communication terminal device; adaptively allocating the weights of the direct total trust value and the indirect total trust value, determining the weight allocation value, and correcting the weight allocation value according to the interactive information utility value of the electric power wireless communication terminal to obtain the corrected weight allocation value; according to the corrected weight allocation value, performing secondary weight allocation on the direct total trust value and the indirect total trust value to determine the device trust of the electric power wireless communication terminal. Aiming at the trust problem of the electric power wireless private network communication terminal, the present invention first determines the direct trust value, and introduces the indirect trust value to make up for the inaccurate direct trust judgment problem, and improves the accuracy of the trust judgment through the comprehensive evaluation of the two.

Description

Technical Field

[0001] The present invention relates to the technical field of power wireless communication terminals, and more specifically, to a method and system for calculating an initialization security state of a power Internet of Things wireless terminal device based on hybrid information entropy. Background Art

[0002] The power Internet of Things is an important driving part of the construction of the energy Internet, which realizes the interconnection and interoperability of various links of the power system, such as "generation, transmission, transformation, distribution, use and dispatch", and human-machine interaction through advanced modern communication information technologies such as big data, cloud computing, the Internet of Things, and mobile communications. There are a large number of terminal devices in the power Internet of Things, which have functions such as data collection, transmission, processing, and storage. They are numerous and complex in variety, and sometimes do not even belong to the same subsystem. With the continuous development of the power Internet of Things, the security threats faced by terminal devices are increasing. In some cases, counterfeit terminals or damaged terminals will disguise their identities, capture keys, and convert them into legitimate terminals to invade the system, destroying its availability and integrity, causing great damage to the power system.

[0003] In terms of IoT network security, internal attacks on IoT are much more harmful than external attacks. Internal attacks are initiated by malicious terminals or denial-of-service terminals in the network. In recent years, trust management has been considered as one of the effective protection mechanisms to ensure network security and an effective way to resist internal attacks. It evaluates the trust value of the terminal based on the historical behavior of the terminal, thereby estimating its credibility in performing specific tasks. Although preliminary research has been carried out, there are still some shortcomings. For example, researchers have improved the accuracy of trust evaluation by improving trust management based on beta distribution and binomial distribution. However, both of them use subjective allocation of trust factors, which will lead to inaccurate trust evaluation. Summary of the invention

[0004] In view of the above problems, the present invention provides a method for calculating the initialization security state of a power Internet of Things wireless terminal device based on hybrid information entropy, comprising:

[0005] Obtain trust and index data of the power wireless communication terminal, fit the trust function according to the exponential distribution function, and determine the direct total trust value of the power wireless communication terminal device;

[0006] Collect transaction record data between the power wireless communication terminal and the public neighbor terminal, and determine the indirect total trust value of the power wireless communication terminal device based on the transaction record data;

[0007] Adaptively assign weights of the direct total trust value and the indirect total trust value, determine the weight assignment value, and modify the weight assignment value according to the interactive information utility value of the power wireless communication terminal to obtain a modified weight assignment value;

[0008] According to the revised weight distribution value, a secondary weight distribution is performed on the direct total trust value and the indirect total trust value to determine the device trust of the power wireless communication terminal.

[0009] Optionally, determining a direct total trust value of the power wireless communication terminal device includes:

[0010] Obtain trust distribution and index distribution data from the trust and index data of the power wireless communication terminal, fit the trust distribution and index distribution data, obtain a trust and credibility model, and determine a cooperation probability function model between terminals based on the trust and credibility model;

[0011] According to the cooperation probability function model between terminals, the trust and reputation model of the trust system node based on probability distribution is determined, and according to the trust model and reputation model based on probability distribution, the trust and reputation evaluation system model is established;

[0012] According to the trust and reputation evaluation system model, the direct total trust value of the power wireless communication terminal equipment is determined.

[0013] Optionally, the transaction record data includes successful transaction record data and failed transaction record data.

[0014] Optionally, the interaction data between terminals in the cooperation probability function model between terminals is maintained for l+m times.

[0015] Optionally, the function in the cooperation probability function model between terminals is a monotonically decreasing function.

[0016] The present invention also proposes an initialization security state calculation system for a power Internet of Things wireless terminal device based on hybrid information entropy, comprising:

[0017] A direct trust value acquisition module is used to acquire the trust and index data of the electric power wireless communication terminal, and determine the direct total trust value of the electric power wireless communication terminal device based on the trust and index data;

[0018] The indirect trust value acquisition module collects transaction record data between the power wireless communication terminal and the public neighbor terminal, and determines the indirect total trust value of the power wireless communication terminal device based on the transaction record data;

[0019] The weight allocation module adaptively allocates the weights of the direct total trust value and the indirect total trust value, determines the weight allocation value, and modifies the weight allocation value according to the interactive information utility value of the power wireless communication terminal to obtain the modified weight allocation value;

[0020] The device trust acquisition module performs secondary weight distribution on the direct total trust value and the indirect total trust value according to the revised weight distribution value, so as to determine the device trust of the power wireless communication terminal.

[0021] Optionally, determining a direct total trust value of the power wireless communication terminal device includes:

[0022] Obtain trust distribution and index distribution data from the trust and index data of the power wireless communication terminal, fit the trust distribution and index distribution data, obtain a trust and credibility model, and determine a cooperation probability function model between terminals based on the trust and credibility model;

[0023] According to the cooperation probability function model between terminals, the trust and reputation model of the trust system node based on probability distribution is determined, and according to the trust model and reputation model based on probability distribution, the trust and reputation evaluation system model is established;

[0024] According to the trust and reputation evaluation system model, the direct total trust value of the power wireless communication terminal equipment is determined.

[0025] Optionally, the transaction record data includes successful transaction record data and failed transaction record data.

[0026] Optionally, the interaction data between terminals in the cooperation probability function model between terminals is maintained for l+m times.

[0027] Optionally, the function in the cooperation probability function model between terminals is a monotonically decreasing function.

[0028] Aiming at the trust problem of power wireless private network communication terminals, the present invention first determines the direct trust value, and introduces the indirect trust value to make up for the inaccurate direct trust judgment problem, and improves the accuracy of trust judgment through comprehensive evaluation of the two. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a flow chart of a method for calculating the initialization security state of a power Internet of Things wireless terminal device based on hybrid information entropy according to the present invention;

[0030] Figure 2 This is a diagram of the wireless private network remote communication architecture of the electric information collection system according to an embodiment of the present invention;

[0031] Figure 3 Establishing a path map for indirect trust of a terminal in an embodiment of the present invention;

[0032] Figure 4 This is a terminal trust evaluation diagram under a selective forwarding attack according to an embodiment of the present invention;

[0033] Figure 5 This is a terminal trust evaluation diagram under a switch attack according to an embodiment of the present invention;

[0034] Figure 6 This is a terminal trust evaluation diagram under a defamation attack according to an embodiment of the present invention;

[0035] Figure 7 This is a terminal trust evaluation diagram under a defamation attack according to an embodiment of the present invention;

[0036] Figure 8 This is a structural diagram of an initialization safety state calculation system for a power Internet of Things wireless terminal device based on hybrid information entropy according to the present invention. DETAILED DESCRIPTION

[0037] Now, exemplary embodiments of the present invention are described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms used in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention. In the accompanying drawings, the same units / elements are marked with the same reference numerals.

[0038] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0039] The present invention provides a method for calculating the initialization security state of a power Internet of Things wireless terminal device based on hybrid information entropy. Figure 1 As shown, including:

[0040] Obtaining trust and index data of the electric power wireless communication terminal, and determining a direct total trust value of the electric power wireless communication terminal device based on the trust and index data;

[0041] Collect transaction record data between the power wireless communication terminal and the public neighbor terminal, and determine the indirect total trust value of the power wireless communication terminal device based on the transaction record data;

[0042] Adaptively assign weights of the direct total trust value and the indirect total trust value, determine the weight assignment value, and modify the weight assignment value according to the interactive information utility value of the power wireless communication terminal to obtain a modified weight assignment value;

[0043] According to the revised weight distribution value, a secondary weight distribution is performed on the direct total trust value and the indirect total trust value to determine the device trust of the power wireless communication terminal.

[0044] Among them, determining the direct total trust value of the power wireless communication terminal equipment trust includes:

[0045] Obtain trust distribution and index distribution data from the trust and index data of the power wireless communication terminal, fit the trust distribution and index distribution data, obtain a trust and credibility model, and determine a cooperation probability function model between terminals based on the trust and credibility model;

[0046] According to the cooperation probability function model between terminals, the trust and reputation model of the trust system node based on probability distribution is determined, and according to the trust model and reputation model based on probability distribution, the trust and reputation evaluation system model is established;

[0047] According to the trust and reputation evaluation system model, the direct total trust value of the power wireless communication terminal equipment is determined.

[0048] The transaction record data includes successful transaction record data and failed transaction record data.

[0049] The interaction data between terminals in the cooperation probability function model between terminals is maintained for l+m times.

[0050] Among them, the function in the cooperation probability function model between terminals is a monotonically decreasing function.

[0051] The present invention will be further described below in conjunction with embodiments:

[0052] Obtain trust and index data of the power wireless communication terminal, and determine the direct total trust value of the power wireless communication terminal device based on the trust and index data, including:

[0053] First, establish a trust model for power wireless communication terminals. The wireless communication terminal architecture is as follows: Figure 2 As shown, the cooperation probability function model between terminals includes:

[0054] According to the fitting of the trust distribution of power wireless communication terminals and the exponential distribution, the expressions of terminal trust and reputation are obtained. The interaction between terminals is set to be (l+m) times, and the cooperation probability function modeling between terminals is obtained. The model is as follows:

[0055]

[0056] According to the above cooperation probability model between terminals, terminal i holds the reputation R of terminal j. ij , where l represents the number of successful interactions and m represents the number of failed interactions. The formula is as follows:

[0057]

[0058] f(p) is the probability distribution function of reputation p. The maximum value of the function represents the maximum probability of reputation p. At this time, the maximum value of the function is defined as the trust value of the terminal. Among them, f'(p) represents the derivative of f(p), T ij It indicates that terminal i holds the trust value of terminal j. The formula is as follows:

[0059]

[0060] It is proved that no matter how the number of malicious terminals increases, trust will still converge. The formula is as follows:

[0061]

[0062] The above trust function is bounded. To verify the monotonicity of the function, T'ij < 0, indicating that the function is strictly monotonically decreasing. According to the theorem of monotonic convergence, no matter how the number of malicious terminals increases, the trust function will still converge.

[0063] Second, establish a trust and reputation evaluation system model, including:

[0064] The above trust model of the power wireless communication terminal is used to obtain the expressions of the terminal reputation and trust based on exponential distribution, and then a trust and reputation system is established to realize trust evaluation. The establishment of the direct trust evaluation model of the power wireless communication terminal includes:

[0065] Direct trust calculation, the formula is as follows:

[0066]

[0067] Among them, D ij Represents the direct trust evaluation value of terminal j to terminal i.

[0068] The N terminal interaction data records recorded by the sliding window of the trust calculation formula are divided into n time slots, and each time slot is numbered in sequence. The forgetting factor ut is introduced to measure the impact of malicious behavior. Calculate the number of successful interactions at the end of the time slot using the following formula:

[0069]

[0070] The number of failed interactions is as follows:

[0071]

[0072] Then the updated trust value is obtained, the formula is as follows:

[0073]

[0074] Direct trust judgment, let H(D ij) is the directly observed entropy, and thr is the threshold of uncertainty. When thr ≤ H(D ij ) ≤ 1, more relevant information is required for the terminal evaluation, and indirect trust is introduced. When H(D ij ) < thr, the total trust of terminal j can be simply set to the direct trust value, that is, the total trust OT ij = D ij .

[0075] Collect the transaction record data of the power wireless communication terminal and the public neighbor terminal. According to the transaction record data, determine the indirect total trust value of the power wireless communication terminal device trust. The establishment of the indirect trust link is as Figure 3 shown as follows:

[0076] Let the successful interaction records observed by the public neighbor terminal be as follows:

[0077]

[0078] The failed interaction records observed by the public neighbor terminal are as follows:

[0079]

[0080] Then the recommendation provided by the public neighbor terminal k is as follows:

[0081]

[0082] The trust degree of terminal i in the recommender k is expressed as:

[0083]

[0084] Suppose there are r intermediate terminals, and the trust values held by terminal i are marked as T i1 …, T i(r-1) , T ir .

[0085] If T ik ≥ x, then use the advice of terminal k , otherwise ignore it.

[0086] Where x (0 ≤ x ≤ 1) is a custom threshold, and k = 1, 2…r.

[0087] Allocate weights according to the trust degree of the recommender as follows:

[0088]

[0089] Then the indirect trust is:

[0090]

[0091] Adaptively assign weights of the direct total trust value and the indirect total trust value, determine the weight assignment value, and modify the weight assignment value according to the interactive information utility value of the power wireless communication terminal to obtain a modified weight assignment value;

[0092] In order to avoid subjective direct weight allocation, the weights of direct trust and indirect trust are adaptively allocated to the terminal trust value based on information entropy, and the utility value of the interactive information provided by the terminal is used to modify the weight allocation value. The specific steps are as follows:

[0093] Calculate the direct trust information entropy value H(D ij )=-D ij log 2 D ij -(1-D ij )log 2 (1-D ij ).

[0094] Calculate the indirect trust information entropy value H(ID ij )=-ID ij log 2 ID ij -(1-ID ij )log 2 (1-ID ij ).

[0095] Request direct trust weight

[0096] Find the indirect trust weight

[0097] The aggregate trust is calculated according to the direct trust determination method as follows:

[0098]

[0099] Among them, OT ij Indicates the terminal aggregation trust.

[0100] According to the revised weight distribution value, a secondary weight distribution is performed on the direct total trust value and the indirect total trust value to determine the device trust of the power wireless communication terminal.

[0101] The following is an attack scenario inside the power wireless communication private network, and the following is an explanation based on the attack scenario:

[0102] Scenario 1: Selective forwarding attack scenario setting: All terminals are set to be trusted terminals, and information interaction can be achieved between terminals. The selective forwarding attack target selection is set to a random number between [0.6-1.0] to simulate the generation of malicious behavior. As the collection cycle increases, the number of malicious terminal information interaction failures increases, and the trust value decreases rapidly.

[0103] Scenario 2: Switch attack scenario setting: It is assumed that the performance of the first 20 terminal interaction cycles is good to establish a good reputation. A small number of malicious terminals are introduced in the 20th cycle to simulate a switch attack. The attack behavior is removed after the 40th cycle.

[0104] Scenario 3: Defamation attack scenario setting: assume that terminal j is an unreliable terminal, and one of the neighbor terminals between terminal i and terminal j is an unreliable terminal, and the remaining neighbor terminals are reliable terminals.

[0105] Scenario 4 Collusion attack scenario setting: Under the collusion attack, the malicious terminal can act as a normal terminal and continue to work. It is assumed that terminal j is unreliable and there are unreliable neighbor terminals. At the same time, multiple malicious terminals merge their respective interaction times.

[0106] Power Internet of Things terminal devices are vulnerable to multiple security threats such as identity spoofing, information theft, and data tampering. Traditional security methods cannot resist internal network attacks from damaged terminals. The trust evaluation system is an effective mechanism to protect power Internet of Things terminals from internal attacks.

[0107] The present invention is implemented for the above scenario, which includes 100 interoperable communication terminals, including smart meters, charging pile metering devices, pole switch controllers, etc., distributed in a 500×500m2 power supply area. Assume that the communication capability of each terminal is the same, the communication radius is 50m, and the size of each data packet is 500bits. To ensure the simplicity of network control, the number of neighbors of each terminal is set to 2 or 3 in the logical connection.

[0108] The present invention simulates the trust evaluation under different initial trust conditions with (l, m) setting values ​​in four different scenarios, and compares it with the binomial trust management BTMS and Beta trust management RFSN algorithms.

[0109] like Figure 4 As shown, the terminal trust is evaluated by the method of the present invention, BTMS and RFSN in scenario 1.

[0110] The solid line indicates that the trust value of a reliable terminal gradually increases with the collection cycle, and the dotted line indicates that the trust value of a malicious terminal gradually decreases with the collection cycle. Figure 4It can be seen that the method of the present invention and the other two methods can distinguish between reliable terminals and malicious terminals, but the method of the present invention has a faster convergence speed. In the 50th cycle, the trust value of the reliable terminal of the method of the present invention is 0.9719, the trust value of the reliable terminal of the BTMS is 0.9516, and the trust value of the reliable terminal of the RFSN is 0.9276;

[0111] At the same time, the method of the present invention evaluates that the trust value of malicious terminals is 0.027, the trust value of BTMS malicious terminals is 0.037, and the trust value of RFSN reliable terminals is 0.075.

[0112] The trust evaluation accuracy of the algorithm of the present invention is improved by 2.13% and 4.78% respectively compared with BTMS and RFSN in terms of the trust evaluation accuracy of reliable terminals; and it is improved by 27.03% and 64.00% respectively compared with BTMS and RFSN in terms of the trust evaluation accuracy of malicious terminals.

[0113] like Figure 5 As shown, the changes in the trust values ​​of the three methods of the present invention, BTMS, and RFSN in resisting switch attacks in scenario 2.

[0114] Depend on Figure 5 It can be seen that the trust values ​​of the three methods are significantly reduced when a switch attack occurs, and the trust values ​​slowly increase after the switch attack ends. However, the trust value of the method of the present invention decreases much faster than that of RFSN and BTMS, which indicates that only a small amount of bad behavior can quickly lead to a loss of trust in a short period of time, indicating that the algorithm of the present invention can detect malicious attacks more sensitively. At the 40th cycle, the terminal trust value of the method of the present invention is 0.1099, the BTMS terminal trust value is 0.2698, and the RFSN terminal trust value is 0.3069.

[0115] like Figure 6 As shown, the changes in the trust values ​​of the three methods of the present invention, BTMS, and RFSN in resisting attacks initiated by unreliable terminals in scenario 3.

[0116] Depend on Figure 6 It can be seen that when an unreliable terminal launches an attack, the terminal trust values ​​of the three methods gradually decrease, but the trust value of the method of the present invention decreases faster than that of RFSN and BTMS, which indicates that the method of the present invention has better response performance in resisting attacks launched by unreliable terminals. In the 50th 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.

[0117] like Figure 7 As shown, the changes in the trust values ​​of the three methods of the present invention, BTMS, and RFSN in resisting collusion attacks in scenario 4 are shown.

[0118] Depend on Figure 7 It can be seen that the terminal trust value of the method of the present invention gradually decreases when a collusion attack occurs, but the terminal trust values ​​of RFSN and BTMS gradually increase with the occurrence of collusion attacks. This shows that the method of the present invention can effectively resist collusion attacks, while the performance of RFSN and BTMS in resisting collusion attacks is poor. In the 30th cycle, the malicious terminal trust value of the method of the present invention is 0.2535, the malicious terminal trust value of BTMS is 0.8267, and the malicious terminal trust value of RFSN is 08484.

[0119] Take the electric power wireless private network communication system composed of electricity consumption information collection terminal equipment, 230 communication terminal, communication base station, core network and business main station as an example.

[0120] There are a large number of remote communication terminals in the wireless communication network for power consumption information collection. A large number of terminals are widely deployed in low-trust environments and are vulnerable to attacks such as slander, switching, defamation, and denial of service initiated by malicious terminals or denial of service terminals in the network. In the trust evaluation process, the method of the present invention is applied to perform trust evaluation on the remote communication terminals in the wireless communication system for power consumption information collection, which mainly includes determining the number of successful interactions between terminals according to the communication time and data volume between the remote terminals, and then firstly performing direct trust judgment on the terminals according to the interactive information between the terminals. When the direct trust value observation entropy value is greater than the set uncertain entropy value, the terminal indirect observation entropy is introduced, and the target terminal is indirectly trusted by introducing a neighbor terminal evaluation mechanism. Finally, the entropy value of direct trust and indirect trust is calculated, and the weight distribution value is corrected by using the utility value of the interactive information provided by the terminal to obtain the aggregated trust value of the remote communication terminal for power consumption information collection. In the trust system verification, four attack modes, namely selective attack, switch attack, defamation attack and collusion attack, were implemented on the 230 communication terminal in the wireless communication remote terminal device for power consumption information collection. The experiment proves that the method proposed in the present invention is suitable for the trust evaluation of the wireless communication terminal for power consumption information collection, and the evaluation method can work normally under different attack modes.

[0121] The present invention also proposes an initialization security state calculation system 200 for a power Internet of Things wireless terminal device based on hybrid information entropy, such as Figure 8 As shown, including:

[0122] A direct trust value acquisition module 201 acquires trust and index data of the electric power wireless communication terminal, and determines a direct total trust value of the electric power wireless communication terminal device based on the trust and index data;

[0123] The indirect trust value acquisition module 202 collects transaction record data between the power wireless communication terminal and the public neighbor terminal, and determines the indirect total trust value of the power wireless communication terminal device based on the transaction record data;

[0124] The weight allocation module 203 adaptively allocates the weights of the direct total trust value and the indirect total trust value, determines the weight allocation value, and modifies the weight allocation value according to the interactive information utility value of the power wireless communication terminal to obtain the modified weight allocation value;

[0125] The device trust acquisition module 204 performs secondary weight distribution on the direct total trust value and the indirect total trust value according to the modified weight distribution value, and determines the device trust of the power wireless communication terminal.

[0126] Among them, determining the direct total trust value of the power wireless communication terminal equipment trust includes:

[0127] Obtain trust distribution and index distribution data from the trust and index data of the power wireless communication terminal, fit the trust distribution and index distribution data, obtain a trust and credibility model, and determine a cooperation probability function model between terminals based on the trust and credibility model;

[0128] According to the cooperation probability function model between terminals, the trust and reputation model of the trust system node based on probability distribution is determined, and according to the trust model and reputation model based on probability distribution, the trust and reputation evaluation system model is established;

[0129] According to the trust and reputation evaluation system model, the direct total trust value of the power wireless communication terminal equipment is determined.

[0130] The transaction record data includes successful transaction record data and failed transaction record data.

[0131] The interaction data between terminals in the cooperation probability function model between terminals is maintained l+m times.

[0132] The function in the cooperation probability function model between terminals is a monotonically decreasing function.

[0133] Aiming at the trust problem of power wireless private network communication terminals, the present invention first determines the direct trust value, and introduces the indirect trust value to make up for the inaccurate direct trust judgment problem, and improves the accuracy of trust judgment through comprehensive evaluation of the two.

[0134] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0135] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0136] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0137] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0138] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0139] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these 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 also intended to include these modifications and variations.

Claims

1. A method for evaluating the trust of a power wireless communication terminal device, the method include: Obtaining trust and index data of the electric power wireless communication terminal, and determining a direct total trust value of the electric power wireless communication terminal device based on the trust and index data; Collect transaction record data between the power wireless communication terminal and the public neighbor terminal, and determine the indirect total trust value of the power wireless communication terminal device based on the transaction record data; Adaptively assign weights of the direct total trust value and the indirect total trust value, determine the weight assignment value, and modify the weight assignment value according to the interactive information utility value of the power wireless communication terminal to obtain a modified weight assignment value; According to the revised weight distribution value, a secondary weight distribution is performed on the direct total trust value and the indirect total trust value to determine the device trust of the power wireless communication terminal; Among them, determining the direct total trust value of the power wireless communication terminal equipment trust includes: Obtain trust distribution and index distribution data from the trust and index data of the power wireless communication terminal, fit the trust distribution and index distribution data, obtain a trust and credibility model, and determine a cooperation probability function model between terminals based on the trust and credibility model; According to the cooperation probability function model between terminals, the trust and reputation model of the trust system node based on probability distribution is determined, and according to the trust and reputation model based on probability distribution, the trust and reputation evaluation system model is established; According to the trust and reputation evaluation system model, the direct total trust value of the power wireless communication terminal equipment is determined; The trust and index data of the electric power wireless communication terminal are obtained, and the direct total trust value of the electric power wireless communication terminal device is determined according to the trust and index data, including: Establish a trust model for power wireless communication terminals, including: According to the fitting of the trust distribution of power wireless communication terminals and the exponential distribution, the expressions of terminal trust and reputation are obtained. The interaction data between terminals is set to be l+m times, and the cooperation probability function modeling between terminals is obtained. The model is as follows: Among them, x is a random variable; p represents reputation; according to the above-mentioned cooperation probability function between terminals, it is modeled that terminal i holds the reputation R of terminal j. ij , where l represents the number of successful interactions and m represents the number of failed interactions. The formula is as follows: f(p) is the cooperation probability function modeling of reputation p. The maximum value of the cooperation probability function modeling represents the maximum probability of reputation p. At this time, the maximum value of the cooperation probability function modeling is defined as the trust value of the terminal, where f'(p) represents the derivative of f(p), T ij It indicates that terminal i holds the trust value of terminal j. The formula is as follows: It is proved that no matter how the number of malicious terminals increases, trust will still converge. The formula is as follows: The probability distribution function of the above reputation p is bounded. To verify the monotonicity of the function, T' ij <0, indicating that the function is strictly monotonically decreasing. According to the monotone convergence theorem, no matter how the number of malicious terminals increases, the trust function will still converge; Establish a trust and reputation evaluation system model, including: The above trust model of the power wireless communication terminal is used to obtain the expressions of the terminal reputation and trust based on exponential distribution, and then a trust and reputation system is established to realize trust evaluation. The establishment of the direct trust evaluation model of the power wireless communication terminal includes: Direct trust calculation, the formula is as follows: Among them, D ij represents the direct trust evaluation value of terminal j to terminal i; The N terminal interaction data records recorded by the sliding window of the direct trust calculation formula are divided into n time slots, and each time slot is numbered in sequence, and the forgetting factor u is introduced t To measure the impact of malicious behavior Where, t is the tth time slot; Calculate the number of successful interactions at the end of the time slot using the following formula: The number of failed interactions is as follows: Then the updated trust value is obtained, the formula is as follows: Let H(D ij ) be the entropy of direct observation, and thr be the threshold of uncertainty. When H(D ij ) < thr, the total trust of terminal j is set to the direct trust value, that is, the total trust OT ij = D ij ; When thr≤H(D ij )≤1, terminal evaluation requires more relevant information and introduces indirect trust; Collect transaction record data between the power wireless communication terminal and the public neighbor terminal, and determine the indirect total trust value of the power wireless communication terminal device based on the transaction record data, as follows: Assume that the successful interaction records observed by the public neighbor terminal are as follows: The failed interaction records observed by the public neighbor terminal are as follows: The recommendation provided by recommender k is as follows: The trust of terminal i to recommender k is expressed as: Assume there are r intermediate terminals, and the trust value held by terminal i is marked as T i1 ,…,T i(r-1) , T ir ; If T ik ≥x, then use the recommendation from recommender k, otherwise ignore it; Where 0≤x≤1 is a custom threshold, k=1,2…r; The weights are assigned based on the trust level of the recommender as follows: The indirect trust is: Adaptively assign weights of the direct total trust value and the indirect total trust value, determine the weight assignment value, and modify the weight assignment value according to the interactive information utility value of the power wireless communication terminal to obtain a modified weight assignment value; In order to avoid subjective direct weight allocation, the weights of direct trust and indirect trust are adaptively allocated to the terminal trust value based on information entropy, and the utility value of the interactive information provided by the terminal is used to modify the weight allocation value. The specific steps are as follows: Calculate the direct trust information entropy value H(D ij )=-D ij log 2 D ij -(1-D ij )log 2 (1-D ij ); Calculate the indirect trust information entropy value H(ID ij )=-ID ij log 2 ID ij -(1-ID ij )log 2 (1-ID ij ); Request direct trust weight Find the indirect trust weight The aggregate trust is calculated according to the direct trust determination method as follows: Among them, OT ij Indicates the terminal aggregation trust.

2. The method according to claim 1, wherein the direct total trust value of the power wireless communication terminal device is determined. include: Obtain trust distribution and index distribution data from the trust and index data of the power wireless communication terminal, fit the trust distribution and index distribution data, obtain a trust and credibility model, and determine a cooperation probability function model between terminals based on the trust and credibility model; According to the cooperation probability function model between terminals, the trust and reputation model of the trust system node based on probability distribution is determined, and according to the trust and reputation model based on probability distribution, the trust and reputation evaluation system model is established; According to the trust and reputation evaluation system model, the direct total trust value of the power wireless communication terminal equipment is determined.

3. According to the method of claim 2, the function in the cooperation probability function model between the terminals is a monotonically decreasing function.

4. A system for evaluating the trust of a power wireless communication terminal device, the system include: A direct trust value acquisition module is used to acquire the trust and index data of the electric power wireless communication terminal, and determine the direct total trust value of the electric power wireless communication terminal device based on the trust and index data; The indirect trust value acquisition module collects transaction record data between the power wireless communication terminal and the public neighbor terminal, and determines the indirect total trust value of the power wireless communication terminal device based on the transaction record data; The weight allocation module adaptively allocates the weights of the direct total trust value and the indirect total trust value, determines the weight allocation value, and modifies the weight allocation value according to the interactive information utility value of the power wireless communication terminal to obtain the modified weight allocation value; The device trust acquisition module performs secondary weight distribution on the direct total trust value and the indirect total trust value according to the modified weight distribution value to determine the device trust of the power wireless communication terminal; Among them, determining the direct total trust value of the power wireless communication terminal equipment trust includes: Obtain trust distribution and index distribution data from the trust and index data of the power wireless communication terminal, fit the trust distribution and index distribution data, obtain a trust and credibility model, and determine a cooperation probability function model between terminals based on the trust and credibility model; According to the cooperation probability function model between terminals, the trust and reputation model of the trust system node based on probability distribution is determined, and according to the trust and reputation model based on probability distribution, the trust and reputation evaluation system model is established; According to the trust and reputation evaluation system model, the direct total trust value of the power wireless communication terminal equipment is determined; The trust and index data of the electric power wireless communication terminal are obtained, and the direct total trust value of the electric power wireless communication terminal device is determined according to the trust and index data, including: Establish a trust model for power wireless communication terminals, including: According to the fitting of the trust distribution of power wireless communication terminals and the exponential distribution, the expressions of terminal trust and reputation are obtained. The interaction data between terminals is set to be l+m times, and the cooperation probability function modeling between terminals is obtained. The model is as follows: Among them, x is a random variable; p represents reputation; according to the above-mentioned cooperation probability function between terminals, it is modeled that terminal i holds the reputation R of terminal j. ij , where l represents the number of successful interactions and m represents the number of failed interactions. The formula is as follows: f(p) is the cooperation probability function modeling of reputation p. The maximum value of the cooperation probability function modeling represents the maximum probability of reputation p. At this time, the maximum value of the cooperation probability function modeling is defined as the trust value of the terminal, where f'(p) represents the derivative of f(p), T ij It indicates that terminal i holds the trust value of terminal j. The formula is as follows: It is proved that no matter how the number of malicious terminals increases, trust will still converge. The formula is as follows: The probability distribution function of the above reputation p is bounded. To verify the monotonicity of the function, T' ij <0, indicating that the function is strictly monotonically decreasing. According to the monotone convergence theorem, no matter how the number of malicious terminals increases, the trust function will still converge; Establish a trust and reputation evaluation system model, including: The above trust model of the power wireless communication terminal is used to obtain the expressions of the terminal reputation and trust based on exponential distribution, and then a trust and reputation system is established to realize trust evaluation. The establishment of the direct trust evaluation model of the power wireless communication terminal includes: Direct trust calculation, the formula is as follows: Among them, D ij represents the direct trust evaluation value of terminal j to terminal i; The N terminal interaction data records recorded in the sliding window of the trust calculation formula are divided into n time slots, and each time slot is numbered in sequence, and the forgetting factor u is introduced t To measure the impact of malicious behavior Where, t is the tth time slot; Calculate the number of successful interactions at the end of the time slot using the following formula: The number of failed interactions is as follows: Then the updated trust value is obtained, the formula is as follows: Let H(D ij ) be the entropy of the direct observation, and thr be the threshold of uncertainty. When H(D ij ) < thr, the total trust of terminal j is set to the direct trust value, i.e., the total trust OT ij = D ij ; When thr≤H(D ij )≤1, terminal evaluation requires more relevant information and introduces indirect trust; Collect transaction record data between the power wireless communication terminal and the public neighbor terminal, and determine the indirect total trust value of the power wireless communication terminal device based on the transaction record data, as follows: Assume that the successful interaction records observed by the public neighbor terminal are as follows: The failed interaction records observed by the public neighbor terminal are as follows: The recommendation provided by recommender k is as follows: The trust of terminal i to recommender k is expressed as: Assume there are r intermediate terminals, and the trust value held by terminal i is marked as T i1 ,…,T i(r-1) , T ir ; If T ik ≥x, then use the recommendation from recommender k, otherwise ignore it; Where 0≤x≤1 is a custom threshold, k=1,2…r; The weights are assigned based on the trust level of the recommender as follows: The indirect trust is: Adaptively assign weights of the direct total trust value and the indirect total trust value, determine the weight assignment value, and modify the weight assignment value according to the interactive information utility value of the power wireless communication terminal to obtain a modified weight assignment value; In order to avoid subjective direct weight allocation, the weights of direct trust and indirect trust are adaptively allocated to the terminal trust value based on information entropy, and the utility value of the interactive information provided by the terminal is used to modify the weight allocation value. The specific steps are as follows: Calculate the direct trust information entropy value H(D ij )=-D ij log 2 D ij -(1-D ij )log 2 (1-D ij ); Calculate the indirect trust information entropy value H(ID ij )=-ID ij log 2 ID ij -(1-ID ij )log 2 (1-ID ij ); Request direct trust weight Find the indirect trust weight The aggregate trust is calculated according to the direct trust determination method as follows: Among them, OT ij Indicates the terminal aggregation trust.

5. The system according to claim 4, wherein the direct total trust value of the power wireless communication terminal device is determined. include: Obtain trust distribution and index distribution data from the trust and index data of the power wireless communication terminal, fit the trust distribution and index distribution data, obtain a trust and credibility model, and determine a cooperation probability function model between terminals based on the trust and credibility model; According to the cooperation probability function model between terminals, the trust and reputation model of the trust system node based on probability distribution is determined, and according to the trust and reputation model based on probability distribution, the trust and reputation evaluation system model is established; According to the trust and reputation evaluation system model, the direct total trust value of the power wireless communication terminal equipment is determined. 6 . The system according to claim 5 , wherein the function in the cooperation probability function model between the terminals is a monotonically decreasing function.

Images