Message reliability evaluation method for aggregation of two trust evaluations in car networking

A vehicle networking and reliability technology, applied in the field of vehicle networking security, can solve problems such as actual performance limitations, ignoring trust, and ignoring data-oriented trust, and achieves the effects of fast evaluation speed, high dynamic characteristics, and accurate evaluation results.

Active Publication Date: 2019-01-11

JINAN UNIVERSITY

7 Cites 10 Cited by

AI-Extracted Technical Summary

Problems solved by technology

[0005] Park et al [S.Park, B.Aslam, and C.C.Zou, "Long-term reputation system for vehicular networking based on vehicle's daily commute routine," inProc.2011CNCC, 2011, pp.436-441.] proposed an infrastructure-based The long-term reputation model of , in which the roadside unit is responsible for monitoring the daily behavior of the vehicle and maintaining its trust information, but this model considers the messages of each message sender in isolation, completely ignoring the data-oriented trust, so its practical performance is limited

Huang et al [Z.Huang, S.Ruj, M...

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Method used

[0085] wherein ID (S) represents the unique identifier of the node S, means that TS (TA, S) represents the time stamp when the trust certificate is generated, and DS (TA, S) represents the digital signature information. Subseque...

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Abstract

The present invention discloses a message reliability evaluation method for aggregation of two trust evaluations in car networking. A trust center is configured to maintain trust information of vehicles, and the vehicles require the newest trust certificates themselves at a fixed period, message publishers carry the newest trust certificates when sending the messages to prove the trustworthiness themselves; a message receiver extracts the trust certificates and integrally considers the message of the plurality of message publishers to determine the reliability after receiving each message, generate one trust feedback for each message publisher and send the trust feedbacks to the trust center, and then the trust center updates the trust feedbacks and locally store the trust feedbacks. The message reliability evaluation method for aggregation of two trust evaluations in car networking can effectively aggregate the two trust evaluations with no need for requiring the trust center by the message receivers in real time so that the evaluation result is more accurate and the evaluation speed is faster, the condition that the vehicles cannot be connected with the trust center in a short time can be compatible, and the message reliability evaluation method for aggregation of two trust evaluations in car networking more accord with the high dynamic features of the car networking.

Application Domain

User identity/authority verificationLocation information based service +1

Technology Topic

Dynamic featureTrustworthiness +3

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Examples

Experimental program(1)

Example Embodiment

[0060] Example

[0061] Attached below figure 1 and attached figure 2 The technical solutions of the present invention are described in detail.

[0062] The technical solution described in the invention mainly includes three elements, namely, the trust center (Trust Authority, TA), the roadside unit (Road-Side Unit, RSU) and the vehicle (ie node, Node), wherein the vehicle and the roadside unit pass through other The vehicle's relay communicates wirelessly, while wired communication is used between the RSU and the trust center.

[0063] The trust center is responsible for maintaining the trust information of the nodes, and updating the trust value of each node every time interval Δt.

[0064] Taking the calculation of the trust value TV(S) of the node S as an example, the trust center first selects the latest at most n pieces of trust feedback ( That is, TF(A,S), TF(B,S), TF(C,S), etc.), and the corresponding feedbackers are added to the feedbacker set FS(S) of node S, that is, FS(S)={A ,B,C,…}.

[0065] The format of trust feedback is:

[0066] TF(A,S)=(ID(A),ID(S),TR(A,S),TS(A,S),DS(A,S)), (1)

[0067] Among them, ID(A) and ID(S) represent the unique identifiers of responder A and node S, respectively, and TR(A, S) represents the rating score generated by responder A based on the previous message quality of node S (ie, 0-4 The higher the message quality, the higher the rating score), TS(A,S) represents the timestamp when TF(A,S) was generated, and DS(A,S) represents the digital signature information. The formats of other trust feedback such as TF(B,S), TF(C,S) are consistent with TF(A,S).

[0068] The weights considered in the calculation of the trust value TV(S) include:

[0069] 1) The feedbacker’s trust value weight Wf(A, S): It is determined by the feedbacker A’s trust value, and the calculation formula is:

[0070] Wf(A,S)=TV(A); (2)

[0071] 2) Time decay weight Wt(A, S): exponential decay is performed according to the time difference between the current timestamp TN and the timestamp in the trust feedback, and the calculation formula is:

[0072]

[0073] where λ is the trust decay factor, which controls the decay speed of Wt(A,S) with the time difference.

[0074] If the total number of trust feedbacks about node S is less than η, the trust value TV(S) is set to a smaller initial trust value, namely:

[0075] TV(S)=τ∈[0,1], (4)

[0076] Otherwise, the trust value TV(S) is derived by the following formula:

[0077]

[0078] From formulas (2)-(5), the ranges of Wf(A,S), Wt(A,S) and TV(S) are all [0,1].

[0079] After deriving the value of TV(S), the trust center overwrites the previously stored trust value of node S with it.

[0080] Step S1, each node requests its own latest trust certificate (Trust Certificate, TC) from the trust center every time interval Δt and after entering the communication range of a certain roadside unit. Taking node S as an example, the format of the request information it sends to the trust center is:

[0081] RQ(S,TA)=(ID(S),TS(S,TA),DS(S,TA)), (6)

[0082] ID(S) represents the unique identifier of node S, TS(S, TA) represents the timestamp when RQ(S, TA) is generated, and DS(S, TA) represents digital signature information.

[0083] After receiving the request information from node S, the trust center first verifies that the request information really comes from node S through DS(S, TA), and retrieves the latest trust value TV(S) of node S in the local storage, and then generates a trust value for it. A certificate in the format:

[0084] TC(TA,S)=(ID(S),TV(S),TS(TA,S),DS(TA,S)), (7)

[0085] Among them, ID(S) represents the unique identifier of the node S, TS(TA,S) represents the timestamp when the trust certificate is generated, and DS(TA,S) represents the digital signature information. Then, the trust center sends TC(TA,S) to node S through the roadside unit, and guarantees its confidentiality through asymmetric encryption. After receiving TC(TA,S), node S updates its local storage for use in sending messages.

[0086] Step S2, when an event E (such as road icing) occurs, the adjacent nodes (such as node S) can witness its occurrence, and broadcast the event to subsequent nodes. Node S is called a witness, also known as a message publisher, and the format of its message is:

[0087] MS(S,E)=(ID(S),MC(S,E),TC(TA,S),TS(S,E),DS(S,E)), (8)

[0088] ID(S) represents the unique identifier of node S, MC(S,E) represents the message content, TC(TA,S) represents the trust certificate of node S, and TS(S,E) represents the timestamp when the message was generated , DS(S,E) represents digital signature information.

[0089] In practice, when an event E occurs, there may be multiple nodes (such as node S, node S', etc.) witnessing its occurrence and reporting it to subsequent nodes. There may be some malicious nodes among these witnessing nodes, they will report the opposite event-E of event E (such as clear road) to the following nodes to deceive other nodes. Therefore, when a node evaluates the reliability of event E, it should simultaneously consider multiple messages from different message senders reporting event E or its opposite event-E to improve the evaluation reliability.

[0090] When a node (ie, a message receiver, such as node R) receives a message reporting an event E or its opposite event-E, its specific strategy is determined according to the distance DT(R, E) between it and the place where the event occurs.

[0091] like figure 2 As shown, three distances are set near the event location, namely the maximum recognition distance, the maximum decision distance and the maximum influence distance:

[0092] 1) When DT(R, E) is greater than the maximum influence distance, node R directly discards the message reporting event E or its opposite event-E;

[0093] 2) When DT(R, E) is between the maximum decision distance and the maximum influence distance, node R verifies the digital signature information in the received message and stores the message reporting event E or its opposite event-E;

[0094] 3) When DT(R, E) is between the maximum recognition distance and the maximum decision distance, the node R makes a comprehensive decision according to a plurality of received messages from different nodes of the report event E or its opposite event-E;

[0095] 4) When DT(R, E) is less than or equal to the maximum recognition distance, node R is able to witness the actual state of event E and rate the quality of previously received messages.

[0096] In the above case 3), set multiple message publishers as node S, node S', etc., and the set is represented as SS(E), that is, SS(E)={S,S',...}, and the number of its elements is denoted as SS(E) is |SS(E)|, the corresponding messages are MS(S,E), MS(S',E), etc. The report event E and the opposite event -E are represented by 1 and -1, respectively.

[0097] The message receiver R considers the following weights when calculating the comprehensive trust value TV(R, E) of the event E:

[0098]1) The weight of the message publisher's trust value Ws(R, S, E): It is determined by the trust value of the message publisher extracted from the trust certificate. The calculation formula is:

[0099] Ws(R,S,E)=TV(S); (9)

[0100] 2) Time decay weight Wc(R, S, E) of the trust certificate: exponential decay is performed according to the time difference between the current timestamp TN and the timestamp in the trust certificate. The calculation formula is:

[0101]

[0102] in is the trust decay factor, which controls the decay speed of Wc(R,S,E) with time difference;

[0103] 3) The time decay weight of the message Wm(R, S, E): exponential decay is performed according to the time difference between the current timestamp TN and the timestamp in the message. The calculation formula is:

[0104]

[0105] where ψ is the trust decay factor, which controls the decay speed of Wm(R, S, E) with the time difference.

[0106] The value of TV(R,E) is derived by the following formula:

[0107]

[0108] From formulas (9)-(12), it can be obtained that Ws(R,S,E), Wc(R,S,E), Wm(R,S,E) are in the range of [0,1], while TV( R,E) in the range [-1,1].

[0109] 1) If TV(R, E)>0, node R trusts event E, and considers that all messages reporting event E are reliable, and all messages reporting event-E are unreliable. Furthermore, node R takes action in accordance with the message reporting event E.

[0110] 2) If TV(R, E)<0, node R trusts event-E, and considers that all messages reporting event-E are reliable, and all messages reporting event E are unreliable. Furthermore, node R takes action in accordance with the message reporting event-E.

[0111] 3) If TV(R, E)=0 (this situation rarely occurs in practice), node R does not trust event E and event-E, and considers all messages reporting event E and event-E to be unreliable. Furthermore, node R takes no action.

[0112] Step S3, when the distance between the message receiver R and the place where the event occurs is less than or equal to the maximum recognition distance, the actual state of the event E can be witnessed, and the quality of each previously received message can be rated, and published for each message at the same time. The author generates a trust feedback whose format is shown in formula (1). In addition, when the message receiver R enters the communication range of a certain roadside unit, it sends the trust feedback to the trust center, and then the trust center verifies its signature information and updates the local storage.

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Message reliability evaluation method for aggregation of two trust evaluations in car networking

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Problems solved by technology

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Abstract

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