Secure interaction method and related equipment

Abstract

The application provides a method for safe interaction and related equipment. The method comprises the following steps: calculating a trust degree based on a transmission rate between nodes; calculating a link reliability based on a transmission parameter of a link between nodes; performing fuzzy and de-fuzzy processing on the trust degree and the link reliability to obtain a connection trust between nodes; and performing interaction between the nodes based on the connection trust. The embodiments of the application can more accurately reflect the trust relationship between the participants by constructing a complete trust confirmation mechanism, considering the trust degree of multiple evaluation dimensions between different participants in a weight distribution manner, and further ensuring that the nodes can confirm the trust degree of each other, establishing a stable interaction environment, and effectively ensuring the safety during interaction.

Description

Technical Field

[0001] The present application relates to the technical field of electric power Internet of Things, and in particular to a method for secure interaction and related equipment. Background Art

[0002] When it comes to the transmission and sharing of energy information data, ensuring secure interaction between terminals has become a crucial issue. This is not only of theoretical significance but also holds broad promise in terms of practical social value. In particular, the rapid access of terminal devices and secure interaction at the system consensus level are crucial. With the addition of numerous new elements, the complexity of the power system has increased significantly. The structure and operation of smart grid systems are becoming increasingly complex, and operational risks in the face of extreme events are rising.

[0003] However, existing consensus algorithms present several challenges. While they offer some degree of fault tolerance, they typically require significant computational resources, resulting in high operational costs. These algorithms can also incur high latency, making data exchange relatively slow in certain scenarios. Furthermore, these algorithms are not suitable for environments requiring Byzantine fault tolerance. This means that in the presence of malicious nodes or attack threats, these algorithms cannot guarantee data integrity and security. Summary of the Invention

[0004] In view of this, the purpose of this application is to propose a secure interaction method and related equipment.

[0005] Based on the above objectives, this application provides a method for secure interaction, including:

[0006] The trust is calculated based on the transmission rate between nodes;

[0007] Based on the transmission parameters of the link between nodes, the link reliability is calculated;

[0008] Performing fuzzification and defuzzification processing on the trust degree and the link reliability to obtain connection trust between nodes;

[0009] Based on the connection trust, the nodes interact with each other.

[0010] In a possible implementation, calculating the trust level based on the transmission rate between nodes includes:

[0011] Calculating a distributed trust value between nodes based on the transmission rate;

[0012] Calculating a joint trust value between nodes based on the distributed trust value;

[0013] The trust degree is calculated based on the distributed trust value and the joint trust value.

[0014] In a possible implementation, the transmission parameters include: the number of successful transmissions and the number of attempted transmissions;

[0015] The link reliability is calculated based on the transmission parameters of the link between the nodes, including:

[0016] The link reliability is calculated based on the number of successful transmissions and the number of attempted transmissions.

[0017] In a possible implementation, the calculating the joint trust value between nodes based on the distributed trust value includes:

[0018] Calculating confidence in reliable interaction between nodes based on the distributed trust value;

[0019] Calculating the unconfidence of reliable interaction between nodes based on the confidence;

[0020] Calculating the uncertainty of reliable interaction between nodes by combining the confidence and the distrust;

[0021] The joint trust value is calculated based on the uncertainty.

[0022] In a possible implementation, the trust level is calculated using the following formula:

[0023] ST (A,B) =θ×DT (A,B) +(1-θ)×JT (A,B)

[0024] Among them, ST (A,B) represents the trust degree, θ represents the weight of the distributed trust value, DT (A,B) Represents the distributed trust value, JT (A,B) Represents the joint trust value.

[0025] In a possible implementation, the link reliability is calculated using the following formula:

[0026]

[0027] Among them, Rel(T) (A,B) Indicates link reliability, tc indicates the number of transmission attempts, and sc indicates the number of successful transmissions.

[0028] In one possible implementation, the uncertainty is calculated using the following formula:

[0029]

[0030] in, represents uncertainty, Indicates confidence, Indicates lack of confidence.

[0031] Based on the same inventive concept, an embodiment of the present application further provides a secure interaction device, including:

[0032] Trust module, used to calculate the trust level based on the transmission rate between nodes;

[0033] Reliability module, used to calculate link reliability based on the transmission parameters of the link between nodes;

[0034] a fuzzy module, configured to perform fuzzy and defuzzification processing on the trust degree and the link reliability to obtain connection trust between nodes;

[0035] The interaction module is used for interacting between nodes based on the connection trust.

[0036] Based on the same inventive concept, an embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and runnable on the processor, wherein when the processor executes the program, a method for secure interaction as described in any one of the above items is implemented.

[0037] Based on the same inventive concept, an embodiment of the present application further provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable the computer to execute any of the above-mentioned secure interaction methods.

[0038] As can be seen from the above, the secure interaction method and related devices provided by this application calculate trust based on the transmission rate between nodes; calculate link reliability based on the transmission parameters of the links between nodes; perform fuzzification and defuzzification on the trust and link reliability to obtain connection trust between nodes; and interact between nodes based on this connection trust. The embodiments of this application divide the secure interaction process into a consensus process and a trust process, wherein the trust process is divided into five stages: distributed trust calculation, joint trust calculation, total trust calculation, connection trust evaluation, and fuzzy trust calculation. First, node trust calculation includes distributed trust calculation and joint trust calculation. Distributed trust calculation involves direct trust calculation between nodes, evaluating trust based on their interaction behavior and information. In this way, the trust value of a node can be dynamically adjusted to reflect the trustworthiness of its behavior. Node trust calculation is a key step and includes distributed trust calculation and joint trust calculation. Distributed trust calculation involves direct trust calculation between nodes, evaluating trust based on their interaction behavior and information. In this way, the trust value of a node can be dynamically adjusted to reflect the trustworthiness of its behavior. In addition, the architecture also considers link reliability and fuzzy trust calculation in connection trust evaluation. Fuzzy trust calculation uses fuzzy logic operation functions to infer the trust between nodes, and through reasonable deduction and synthesis, converts fuzzy trust into appropriate clear output. In addition, the calculation process of the technical solution of the embodiment of the present application is not complicated, and does not require multiple rounds of trust calculation and confirmation, which can effectively save computing resources and save operating costs. The technical solution of the present application has a low delay, which can ensure the progress of data interaction and can be applied to environments that require Byzantine fault tolerance. In the presence of malicious nodes or attack threats, the embodiment of the present application can ensure the integrity and security of the data. Therefore, the secure interaction method of the embodiment of the present application realizes safe and efficient cross-domain information exchange for equipment in different fields in the power system, ensures secure information interaction between heterogeneous equipment, and improves the transmission reliability and privacy of power enterprise data. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in this application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are merely embodiments of this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0040] Figure 1 A schematic diagram of a secure interaction method flow diagram according to an embodiment of the present application;

[0041] Figure 2 This is a schematic diagram of the security system model architecture of an embodiment of the present application;

[0042] Figure 3 A schematic diagram of the security domain boundary and trust management architecture of an embodiment of the present application;

[0043] Figure 4 A schematic diagram of the structure of a secure interaction device according to an embodiment of the present application;

[0044] Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to make the objectives, technical solutions and advantages of this application more clear, this application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0046] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should have the usual meanings understood by people with ordinary skills in the field to which this application belongs. The "first", "second" and similar words used in the embodiments of the present application do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0047] As mentioned in the background section, secure interaction between terminals has become a critical issue in the transmission and sharing of energy information data. This is not only of great theoretical significance but also has broad application prospects in terms of practical social value. In particular, with the introduction of numerous new elements, the complexity of power systems has increased significantly. The structure and operation of smart grid systems are becoming increasingly complex, and operational risks in the face of extreme events are increasing. However, existing consensus algorithms present several challenges. While they offer some degree of fault tolerance, they typically require significant computing resources, resulting in high operating costs. These algorithms can also introduce high latency, making data interaction relatively slow in certain scenarios. Furthermore, these algorithms are not suitable for environments requiring Byzantine fault tolerance. This means that in the presence of malicious nodes or attack threats, these algorithms cannot guarantee data integrity and security.

[0048] Taking the above into consideration, an embodiment of the present application proposes a method for secure interaction. This method calculates trust based on the transmission rate between nodes, calculates link reliability based on the transmission parameters of the links between nodes, performs fuzzification and defuzzification on the trust and link reliability to obtain connection trust between nodes, and then interacts between nodes based on the connection trust. This embodiment of the present application divides the secure interaction process into a consensus process and a trust process, wherein the trust process is divided into five stages: distributed trust calculation, joint trust calculation, total trust calculation, connection trust evaluation, and fuzzy trust calculation. First, node trust calculation includes distributed trust calculation and joint trust calculation. Distributed trust calculation involves direct trust calculation between nodes, evaluating trust based on their interaction behavior and information. In this way, the trust value of a node can be dynamically adjusted to reflect the trustworthiness of its behavior. Node trust calculation is a key step and includes distributed trust calculation and joint trust calculation. Distributed trust calculation involves direct trust calculation between nodes, evaluating trust based on their interaction behavior and information. In this way, the trust value of a node can be dynamically adjusted to reflect the trustworthiness of its behavior. Furthermore, this architecture also considers link reliability and fuzzy trust calculation in connection trust evaluation. Fuzzy trust calculation uses fuzzy logic operation functions to infer the trust between nodes, and through reasonable deduction and synthesis, converts fuzzy trust into appropriate clear output. In addition, the calculation process of the technical solution of the embodiment of the present application is not complicated, and does not require multiple rounds of trust calculation and confirmation, which can effectively save computing resources and save operating costs. The technical solution of the present application has a low delay, which can ensure the progress of data interaction and can be applied to environments that require Byzantine fault tolerance. In the presence of malicious nodes or attack threats, the embodiment of the present application can ensure the integrity and security of the data. Therefore, the secure interaction method of the embodiment of the present application realizes safe and efficient cross-domain information exchange for equipment in different fields in the power system, ensures secure information interaction between heterogeneous equipment, and improves the transmission reliability and privacy of power enterprise data.

[0049] The technical solutions of the embodiments of the present application are described in detail below through specific examples.

[0050] refer to Figure 1 The secure interaction method of the embodiment of the present application includes the following steps:

[0051] Step S101, calculating the trust degree based on the transmission rate between nodes;

[0052] Step S102, calculating link reliability based on transmission parameters of the link between nodes;

[0053] Step S103, performing fuzzification and defuzzification processing on the trust degree and the link reliability to obtain connection trust between nodes;

[0054] Step S104: Based on the connection trust, the nodes interact with each other.

[0055] refer to Figure 2 , is a schematic diagram of the security system model architecture of an embodiment of the present application.

[0056] like Figure 2 As shown, first, it is necessary to read the grid interaction data, construct a platform, set up multiple domains, and interact between domains in a secure manner.

[0057] Specifically, to address resource change security requirements and build multi-level collaborative security domains, the HotStuff consensus framework can help build a platform that enables secure and efficient interaction between different terminal domains. Each security domain defines a set of device, service, and network resource boundaries within the system. Participants within these boundaries have security policies and access control rules. This framework is based on blockchain technology for maintaining and monitoring smart grid terminal devices. By defining clear boundaries, it can achieve secure isolation and boundary protection between participants. The HotStuff algorithm is a partial synchronization model based on the Byzantine problem of the leader node. Once the network enters the synchronous state, the HotStuff algorithm will allow a leader node to initiate consensus according to a certain frequency (such as the maximum network latency). The network communication overhead of this algorithm is linearly related to the number of replicas.

[0058] Afterwards, each security domain demarcates a set of devices, services, and network resources in the system, and the parties within this boundary have security policies and access control rules;

[0059] Specifically, the participants within this boundary have security policies and access control rules. Each security domain in the system represents a specific scope, encompassing a set of devices, services, and network resources. Within this scope, a set of security policies and access control rules are established to ensure that all parties involved can access and interact in a prescribed manner. These security policies and rules help maintain the overall security of the system, ensuring that sensitive data and critical resources are protected from unauthorized access or threats.

[0060] Trust management is then divided into two modules: inter-domain node trust calculation and connection trust assessment calculation. These two modules provide reliable communication trust management support for data interaction.

[0061] Specifically, in the embodiments of the present application, the simulation experiment adopts a hybrid attack and defense experiment to evaluate the ability of the proposed Host-based Intrusion Detection System (HIDS) to resist malicious attacks. We place the series of consensus algorithms in a malicious situation to evaluate their performance and compare the robustness of different algorithms. We consider different attack scenarios and parameter settings, and the experiment is pre-set with 30 nodes (node, malicious node ∈ [0, 50]), when (node, trust threshold ∈ [0, 60]), each experiment is pre-set for 60 rounds of consensus, and the number of nodes in each round of the experiment is 10, 20, 30, 40, 50, 60, and the client sends 1000 interaction requests in parallel.

[0062] Reference Figure 3 , the security domain boundary and trust management architecture diagram of the embodiments of the present application.

[0063] As Figure 3 shown, for step S101, the trust degree is calculated based on the transmission rate between nodes.

[0064] In some embodiments, the trust degree is calculated based on the transmission rate between nodes, including: calculating a distributed trust value between nodes based on the transmission rate; calculating a joint trust value between nodes based on the distributed trust value; and calculating the trust degree based on the distributed trust value and the joint trust value.

[0065] In the embodiments of the present application, the distributed trust calculation in node trust calculation: at the beginning of the transaction, the node will show cooperative behavior and actively participate in data transmission. Node A will calculate the direct trust degree DT based on the observation of the behavior of node B in the hybrid attack and defense mode. Then through the distributed trust mechanism, the interaction behavior and information between nodes are collected, and the evaluation of multiple nodes on a certain node is integrated.

[0066] In some embodiments, the distributed trust value between nodes is calculated by the following formula:

[0067]

[0068] wherein DT(A i ,B) represents the distributed trust value between nodes, α and β are trust parameter values, N i represents the transmission rate between nodes, represents a penalty factor.

[0069] In some embodiments, the penalty factor is calculated by the following formula:

[0070]

[0071] in, represents the penalty factor, s represents the estimated successful transactions, and f represents the estimated failed transactions.

[0072] Specifically, where α = s + 1 and β = f + 1, such that s ≥ 0, f ≥ 0, s represents an estimated successful transaction, and f represents an estimated failed transaction. When a transaction is initiated, there is no historical observation data at the beginning, and an initial half-point trust value can be assigned to all network nodes. It is a penalty factor used to reduce the trustworthiness of a node. As the number of misbehaving nodes increases, the factor value will rise, which will cause the trust value of the node to decrease. This effect is achieved by applying a nonlinear penalty factor, which causes the trust value to decrease rapidly as the penalty factor increases. By meeting a certain threshold relationship, these nodes may be penalized and excluded from further transactions.

[0073] Furthermore, in the node trust calculation, a joint trust calculation is performed: Observing node A selects from its neighbors those members whose trust values ​​are greater than a trust threshold (e.g., A1, A2, A3, ..., An) and adds them to the same set. Each node in the set will share the joint trust information of the relevant nodes with node A based on its reliable packet forwarding rate.

[0074] Specifically, there are n participants, each of whom evaluates the other n-1 participants and gives trust scores based on multiple evaluation dimensions. The reliable interaction probability of the trusted node's neighboring node B is calculated to determine whether node B is benign or malicious.

[0075] In some embodiments, the calculation of the joint trust value between nodes based on the distributed trust value includes: calculating the confidence of reliable interaction between nodes based on the distributed trust value; calculating the distrust of reliable interaction between nodes based on the confidence; calculating the uncertainty of reliable interaction between nodes by combining the confidence and the distrust; and calculating the joint trust value based on the uncertainty.

[0076] In some embodiments, the confidence level is calculated using the following formula:

[0077]

[0078] in, Indicates confidence, represents the distributed trust value between nodes, and p represents the probability of reliable interaction.

[0079] In some embodiments, the reliable interaction probability is calculated by the following formula:

[0080]

[0081] Among them, p represents the probability of reliable interaction, max represents the power communication frame interval, N i Indicates the transmission rate between nodes.

[0082] In some embodiments, the uncertainty is calculated by the following formula:

[0083]

[0084] in, Indicates disbelief, represents the distributed trust value between nodes, and p represents the probability of reliable interaction.

[0085] In some embodiments, the uncertainty is calculated using the following formula:

[0086]

[0087] in, represents uncertainty, Indicates confidence, Indicates lack of confidence.

[0088] Furthermore, assuming there are k recommenders, when the calculated difference shows a large deviation, the recommender's trust value will not be used in the calculation of the joint trust.

[0089] In some embodiments, the calculation of the joint trust value between nodes based on the distributed trust value includes: calculating the confidence of reliable interaction between nodes based on the distributed trust value; calculating the distrust of reliable interaction between nodes based on the confidence; calculating the uncertainty of reliable interaction between nodes by combining the confidence and the distrust; and calculating the joint trust value based on the uncertainty.

[0090] In some embodiments, the joint trust value is calculated using the following formula:

[0091]

[0092] Among them, JT (A,B) represents the joint trust value, k represents the number of recommenders, represents uncertainty, Represents a set, a node selects members whose trust value is greater than the trust threshold from its neighbors to form the set, t represents A value in the collection.

[0093] Specifically, when the calculated differences show significant deviation, the recommender's trust value will not be included in the calculation of the joint trust. The joint trust is calculated based on the formula of node A on node B to eliminate unnecessary duplication of information and ensure the accuracy of the calculation.

[0094] Furthermore, the total trust calculation in the node trust calculation is: observe node A, add the direct trust and indirect trust based on the weight to calculate the overall trust ST of the observation node B (A,B) .

[0095] In some embodiments, the trust level is calculated using the following formula:

[0096] ST (A,B) =θ×DT (A,B) +(1-θ)×JT (A,B)

[0097] Among them, ST (A,B) represents the trust degree, θ represents the weight of the distributed trust value, DT (A,B) Represents the distributed trust value, JT (A,B) Represents the joint trust value.

[0098] Specifically, where 0 ≤ θ ≤ 1, θ and 1-θ are the weights for calculating the distributed trust value and the joint trust value, respectively. The total trust calculation formula comprehensively considers the trust levels of different participants across multiple evaluation dimensions by allocating weights. This application can obtain the overall trust level of the participants, which is used to more accurately reflect the trust relationship between the participants.

[0099] In some embodiments, for step S102, the transmission parameters include: the number of successful transmissions and the number of attempted transmissions; the link reliability is calculated based on the transmission parameters of the link between nodes, including: the link reliability is calculated based on the number of successful transmissions and the number of attempted transmissions.

[0100] Furthermore, the link reliability is evaluated using the connection trust, which is a symbol for evaluating the stability and reliability of the communication channel connection between nodes.

[0101] In some embodiments, the link reliability is calculated using the following formula:

[0102]

[0103] Among them, Rel(T) (A,B) represents the link reliability, t represents the number of transmission attempts, and sc represents the number of successful transmissions.

[0104] Specifically, the number of successful transmissions on the link is sc, the number of attempted transmissions is tc, and A calculates the buffering capacity of the observation node B by recording the number of round-trip transmissions (, that is, the arrival time of the data packet at the observation node B and the time it is received by the observation node A).

[0105] Furthermore, for step S103 and step S104, the fuzzy trust calculation in the connection trust evaluation is as follows:

[0106]

[0107] Among them, FT (p) represents fuzzy trust, n represents the number of fuzzy control rules, ltc i Indicates the output corresponding to the rule, η(ltc i ) indicates the specified ltc i The degree of membership.

[0108] Specifically, the fuzzy logic inference algorithm uses the input parameters of a fuzzy logic operation function and if-then rules to form a fuzzy output by integrating the output results of all fuzzy rules. In this invention, the function rationally infers and synthesizes incomplete or ambiguous confidence levels. We apply the Mamdani fuzzy inference engine to perform fuzzy inference on the overall confidence norm product to obtain the output response. We also use the centroid defuzzification method to obtain the final result. The responses of all fuzzy rules are then aggregated and converted into appropriate clear outputs.

[0109] Furthermore, based on the aforementioned fuzzy operation and defuzzification operation, the final connection trust value of the embodiment of the present application can be finally obtained. After obtaining the final connection trust value, the size relationship between the connection trust value and the preset threshold is determined, and based on the size relationship, it is determined whether an interactive relationship should be established between the two nodes. Of course, if the connection trust value is greater than or equal to the preset threshold, an interactive relationship can be established between the two nodes. If the connection trust is less than the preset threshold, it proves that one of the two nodes may be a malicious node, or the reliability of the link between the two nodes is not sufficient, so an interactive relationship may not be established between the two nodes.

[0110] As can be seen from the above embodiments, the secure interaction method described in the embodiments of this application calculates trust based on the transmission rate between nodes; calculates link reliability based on the transmission parameters of the links between nodes; performs fuzzification and defuzzification on the trust and link reliability to obtain connection trust between nodes; and interacts between nodes based on the connection trust. The embodiments of this application divide the secure interaction process into a consensus process and a trust process, wherein the trust process is divided into five stages: distributed trust calculation, joint trust calculation, total trust calculation, connection trust evaluation, and fuzzy trust calculation. First, node trust calculation includes distributed trust calculation and joint trust calculation. Distributed trust calculation involves direct trust calculation between nodes, evaluating trust based on their interaction behavior and information. In this way, the trust value of a node can be dynamically adjusted to reflect the trustworthiness of its behavior. Node trust calculation is a key step and includes distributed trust calculation and joint trust calculation. Distributed trust calculation involves direct trust calculation between nodes, evaluating trust based on their interaction behavior and information. In this way, the trust value of a node can be dynamically adjusted to reflect the trustworthiness of its behavior. In addition, the architecture also considers link reliability and fuzzy trust calculation in connection trust evaluation. Fuzzy trust calculation uses fuzzy logic operation functions to infer the trust between nodes, and through reasonable deduction and synthesis, converts fuzzy trust into appropriate clear output. In addition, the calculation process of the technical solution of the embodiment of the present application is not complicated, and does not require multiple rounds of trust calculation and confirmation, which can effectively save computing resources and save operating costs. The technical solution of the present application has a low delay, which can ensure the progress of data interaction and can be applied to environments that require Byzantine fault tolerance. In the presence of malicious nodes or attack threats, the embodiment of the present application can ensure the integrity and security of the data. Therefore, the secure interaction method of the embodiment of the present application realizes safe and efficient cross-domain information exchange for equipment in different fields in the power system, ensures secure information interaction between heterogeneous equipment, and improves the transmission reliability and privacy of power enterprise data.

[0111] It should be noted that the method of the embodiment of the present application can be performed by a single device, such as a computer or server. The method of this embodiment can also be applied in a distributed scenario and performed by multiple devices working together. In such a distributed scenario, one of the multiple devices may only perform one or more steps of the method of the embodiment of the present application, and the multiple devices will interact with each other to complete the method.

[0112] It should be noted that the above description is limited to some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in an order different from that described in the above embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0113] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a secure interaction device.

[0114] refer to Figure 4 , the secure interaction device comprises:

[0115] A trust module 41 is configured to calculate a trust degree based on a transmission rate between nodes;

[0116] A reliability module 42 is configured to calculate link reliability based on transmission parameters of links between nodes;

[0117] a fuzzification module 43 for performing fuzzification and defuzzification processing on the trust degree and the link reliability to obtain connection trust between nodes;

[0118] The interaction module 44 is configured to enable nodes to interact with each other based on the connection trust.

[0119] For the convenience of description, the above devices are described as being divided into various modules according to their functions. Of course, when implementing this application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0120] The apparatus of the above embodiment is used to implement the corresponding secure interaction method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0121] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and runnable on the processor, wherein when the processor executes the program, the method of secure interaction described in any of the above embodiments is implemented.

[0122] Figure 510 is a schematic diagram showing a more specific hardware structure of an electronic device provided in this embodiment. The device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are communicatively connected to each other within the device via the bus 1050.

[0123] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0124] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage devices, dynamic storage devices, etc. The memory 1020 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0125] The input / output interface 1030 is used to connect input / output modules to implement information input and output. The input / output modules can be configured as components within the device (not shown in the figure) or can be externally connected to the device to provide corresponding functions. Input devices may include a keyboard, mouse, touch screen, microphone, various sensors, etc., and output devices may include a display, speaker, vibrator, indicator light, etc.

[0126] The communication interface 1040 is used to connect to a communication module (not shown) to enable communication between the device and other devices. The communication module can communicate via a wired method (such as USB, network cable, etc.) or a wireless method (such as mobile network, WiFi, Bluetooth, etc.).

[0127] The bus 1050 comprises a path for transmitting information between the various components of the device (eg, the processor 1010 , the memory 1020 , the input / output interface 1030 , and the communication interface 1040 ).

[0128] It should be noted that although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040, and the bus 1050, in a specific implementation, the device may also include other components necessary for normal operation. In addition, it will be understood by those skilled in the art that the above device may only include the components necessary to implement the embodiments of this specification, and does not necessarily include all the components shown in the figure.

[0129] The electronic device of the above embodiment is used to implement the corresponding secure interaction method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0130] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable the computer to execute the method of secure interaction as described in any of the above embodiments.

[0131] The computer-readable media of this embodiment include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0132] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the method of secure interaction as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0133] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. Within the scope of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0134] In addition, for simplicity of description and discussion, and in order not to make the embodiment of the application difficult to understand, the known power supply / ground connection with integrated circuit (IC) chip and other components may or may not be shown in the accompanying drawings provided. In addition, the device can be shown in the form of a block diagram to avoid making the embodiment of the application difficult to understand, and this also takes into account the following fact, that is, the details of the embodiment of these block diagram devices are highly dependent on the platform to be implemented in the embodiment of the application (that is, these details should be fully within the scope of understanding of those skilled in the art). When specific details (for example, circuit) are set forth to describe exemplary embodiments of the application, it will be apparent to those skilled in the art that the embodiment of the application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0135] Although the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those skilled in the art based on the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may utilize the embodiments discussed.

[0136] The embodiments of the present application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the scope of protection of this application.

Claims

1. A method for secure interaction, characterized in that: include: Calculating the trust degree based on the transmission rate between the nodes includes: calculating a distributed trust value between the nodes based on the transmission rate; calculating a joint trust value between the nodes based on the distributed trust value; and calculating the trust degree based on the distributed trust value and the joint trust value; Calculating link reliability based on transmission parameters of the link between nodes; the transmission parameters include: number of successful transmissions and number of attempted transmissions; Performing fuzzification and defuzzification processing on the trust degree and the link reliability to obtain connection trust between nodes; Based on the connection trust, the nodes interact with each other; The calculating of the joint trust value between nodes based on the distributed trust value includes: Calculating confidence in reliable interaction between nodes based on the distributed trust value; Calculating the unconfidence of reliable interaction between nodes based on the confidence; Calculating the uncertainty of reliable interaction between nodes by combining the confidence and the distrust; Calculating the joint trust value based on the uncertainty; The distributed trust value between the nodes is calculated by the following formula: in, represents the distributed trust value between nodes, and is the trust parameter value, Indicates the transmission rate between nodes, represents the penalty factor; The confidence level is calculated by the following formula: in, Indicates confidence, represents the distributed trust value between nodes, represents the probability of reliable interaction; The uncertainty is calculated by the following formula: in, Indicates disbelief, represents the distributed trust value between nodes, represents the probability of reliable interaction; The uncertainty is calculated using the following formula: in, represents uncertainty, Indicates confidence, Indicates disbelief; The joint trust value is calculated by the following formula: in, represents the joint trust value, Indicates the number of recommenders, represents uncertainty, Represents a set, a node selects members whose trust value is greater than the trust threshold from its neighbors to form the set, express A value in the collection.

2. The method according to claim 1, characterized in that The link reliability is calculated based on the transmission parameters of the link between the nodes, including: The link reliability is calculated based on the number of successful transmissions and the number of attempted transmissions.

3. The method according to claim 1, characterized in that The trust degree is calculated by the following formula: in, Indicates trust, represents the weight of the distributed trust value, represents the distributed trust value, Represents the joint trust value.

4. The method according to claim 1, wherein The link reliability is calculated by the following formula: in, Indicates link reliability, Indicates the number of transmission attempts. Indicates the number of successful transmissions.

5. A secure interaction device using the secure interaction method according to any one of claims 1 to 4, characterized in that: include: Trust module, used to calculate the trust level based on the transmission rate between nodes; Reliability module, used to calculate link reliability based on the transmission parameters of the link between nodes; a fuzzy module, configured to perform fuzzy and defuzzification processing on the trust degree and the link reliability to obtain connection trust between nodes; The interaction module is used for interacting between nodes based on the connection trust.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method according to any one of claims 1 to 4 is implemented.

7. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 4.

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