CN109347852A - A lightweight trust evaluation method for Internet of Vehicles - Google Patents

A lightweight trust evaluation method for Internet of Vehicles Download PDF

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CN109347852A
CN109347852A CN201811315880.6A CN201811315880A CN109347852A CN 109347852 A CN109347852 A CN 109347852A CN 201811315880 A CN201811315880 A CN 201811315880A CN 109347852 A CN109347852 A CN 109347852A
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trust
trustee
lightweight
node
certificate
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CN109347852B (en
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刘志全
翁健
马建峰
李盈
兰奕明
魏凯敏
冯丙文
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Jinan University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/20—Network architectures or network communication protocols for network security for managing network security; network security policies in general
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
    • H04L9/3247—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials involving digital signatures

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  • Mobile Radio Communication Systems (AREA)

Abstract

The invention discloses a kind of car networking method for evaluating trust of lightweight, specifically include step: S1, at the end of node previously interacts, and interaction both sides are that other side generates the trust comprising itself digital signature and proves and send to other side all in accordance with interactive experience；S2, interaction both sides, which receive new trust, proves that posteriority demonstrate,proves its signing messages, and updates and be locally stored to save to trust itself best at most η item and prove, wherein η ∈ Z+For system parameter；S3, it is potential interaction start when, potential interactive both sides by the trust being locally stored proof be sent to other side to prove that itself is believable；S4, potential interactive both sides are verified by digital signature information to be trusted the authenticity proved and exports the trust value of other side accordingly and decide whether to agree to interact, and is interacted when both sides agree to.The present invention does not depend on trust center and roadside unit, more meets extensive, the distributed nature of car networking.

Description

A kind of car networking method for evaluating trust of lightweight
Technical field
The present invention relates to car networking security technology areas, and in particular to a kind of car networking method for evaluating trust of lightweight.
Background technique
Currently, traffic accident, congestion in road and environmental pollution have become the critical issue that global urban is faced, and vehicle joins Net as Internet of Things in the main application of automobile industry and the core component of intelligent transportation system, in urban highway traffic side Face plays vital effect.Car networking is considered as most one of the branch of market potential in Internet of Things, is arranged For national " 12th Five-Year Plan ", the great research project of " 13 " planning outline.
However, due to characteristics such as extensive, open, distributed, sparse and high dynamics, car networking for malicious act and Attack be it is fragile, safety and reliability, which has been increasingly becoming, restricts the bottleneck that further develops of car networking, and is related to vehicle connection Can net be applied in true road environment.Existing scheme mostly uses digital signature and cryptological technique, can not assess section The reliability of point (i.e. vehicle) and the quality of message.
Trust management plays the part of vital role in car networking, it enables each node to assess other sections in advance The trust value of point and message, to avoid serious consequence caused by malicious node and not firm message.Currently, the trust pipe in car networking Reason is still within the primary stage, and only small amounts of trust evaluation scheme is suggested.Based on architecture, existing scheme can be rough Ground is divided into two classes, the i.e. scheme based on infrastructure and self-organizing scheme.
Li et al. people [X.Li, J.Liu, X.Li, and W.Sun, " RGTE:A reputation-based global trust establishment in VANETs,"In Proceedings of the 5th International Conference on Intelligent Networking and Collaborative Systems,2013,pp.210- 214.] propose that a global trusting based on popularity establishes scheme RGTE for car networking, wherein popularity administrative center is responsible for collection The trust information of all legitimate nodes simultaneously calculates its popularity score.The model hypothesis popularity administrative center is completely credible and exists in real time Line, needs higher maintenance cost, and there are the inherent shortcomings such as single point failure, time delay be big.Wei et al. [Z.Wei, F.R.Yu, and A.Boukerche,"Trust based security enhancements for vehicular ad hoc networks,"In Proceedings of the 4th International Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications,2014,pp.103- 109.] comprehensively consider the direct trust based on history interaction and the indirect trust based on trust recommendation, and one is proposed for car networking Kind distributed trust appraisal procedure, is exported wherein directly trusting by Bayesian formula, and is trusted indirectly and led by D-S evidence theory Out.The model needs to apply letter trust recommendation information of person's collection about receiver, it will usually biggish time, bandwidth be caused to disappear Consumption.
Summary of the invention
The purpose of the present invention is to overcome the shortcomings of the existing technology and deficiency, and the car networking trust for providing a kind of lightweight is commented Estimate method, the method does not depend on trust center and roadside unit, more meets extensive, the distributed nature of car networking.
The purpose of the present invention is realized by the following technical solution: a kind of car networking method for evaluating trust of lightweight, tool Body includes the following steps:
S1, node previously interact at the end of, interaction both sides all in accordance with interactive experience be other side generate one include itself The trust of digital signature is proved and is sent to other side；
S2, interaction both sides, which receive new trust, proves that posteriority demonstrate,proves its signing messages, and updates and be locally stored to save to certainly The best at most η item of body, which is trusted, to be proved, wherein η ∈ Z+For system parameter；
S3, it is potential interaction start when, potential interactive both sides by the trust being locally stored proof be sent to other side to demonstrate,prove It is bright that itself is believable；
S4, potential interactive both sides verify the letter trusted the authenticity proved and export other side accordingly by digital signature information Appoint value and decide whether to agree to interact, is interacted when both sides agree to.
Preferably, in the step S1, trusting proves specific format are as follows:
TC (B, A)=(ID (B), ID (A), RT (B, A), WG (B), TS (B, A), DS (B, A))
Wherein B and A indicates node, and B is certifier, and A is receiver；ID (B) and ID (A) respectively indicate certifier B and by The unique identifier of letter person A；RT (B, A) indicates assessed value vector, specific format are as follows:
RT (B, A)=(RT (B, A, 1), RT (B, A, 2) ..., RT (B, A, n))
Wherein n indicates to trust the number of aspect, and RT (B, A, i) (i ∈ [1, n]) indicates certifier B to the i-th of receiver A Assessed value in terms of a trust；WG (B) indicates weighted value vector, specific format are as follows:
WG (B)=(WG (B, 1), WG (B, 2) ..., WG (B, n))
Wherein WG (B, i) (i ∈ [1, n]) indicates that certifier B trusts i-th the interest preference level of aspect；TS(B,A) Indicate timestamp when TC (B, A) is generated；DS (B, A) indicates digital signature information.
Further, the RT (B, A, i) is expressed as linguistic variable, including " very good ", " good ", " general ", " poor " " excessively poor "；The WG (B, i) is expressed as linguistic variable, including " very high ", "high", " in ", " low " and " very low ".
Preferably, in the step S2, it is that the trust itself generated proves TC (B, A) that receiver A, which receives certifier B, Afterwards, it first verifies that its signature information D S (B, A), then judges that the size of the locally stored quantity NM (A) and η for trusting and proving is closed System: if NM (A) < η, receiver A directly store TC (B, A)；If NM (A)=η, receiver A calculate every trust proof pair The weighting assessed value answered, and select accordingly and itself best η item trust proof is stored, while deleting other credentials Bright, the trust that receiver A considers proves to include that TC (B, A) and locally stored η item trust proof.
Preferably, in the step S2, the specific steps of weighting assessed value are calculated by TC (B, A) are as follows:
S2.1, the RT (B, A, i) in TC (B, A) is converted to fuzzy evaluation RF (B, A, i) and clear assessment RC (B, A, I), the wherein specific format of RF (B, A, i) are as follows:
RF (B, A, i)=(RF (B, A, i, 1), RF (B, A, i, 2), RF (B, A, i, 3), RF (B, A, i, 4))
Wherein 0≤RF (B, A, i, 1)≤RF (B, A, i, 2)≤RF (B, A, i, 3)≤RF (B, A, i, 4)≤100；RC(B, A, i) be RF (B, A, i) symbolic distance, can specifically be exported by following formula:
S2.2, WG (B, i) in TC (B, A) is converted into fuzzy weighted values WF (B, i) and clear weight WC (B, i), wherein WF The specific format of (B, i) are as follows:
WF (B, i)=(WF (B, i, 1), WF (B, i, 2), WF (B, i, 3), WF (B, i, 4))
Wherein 0≤WF (B, i, 1)≤WF (B, i, 2)≤WF (B, i, 3)≤WF (B, i, 4)≤10；WC (B, i) can be by following Formula export:
The corresponding fuzzy evaluation value SF (B, A) of S2.3, TC (B, A) can calculate are as follows:
The corresponding clear assessed value SC (B, A) of TC (B, A) can calculate are as follows:
S2.4, receiver A only consider time decaying weight WT (B, A) when the most advantageous trust of selection proves, calculate public Formula are as follows:
Wherein, TN indicates current time stamp；TS (B, A) is contained timestamp in TC (B, A)；ω indicates that time window is big It is small；θ is time decay factor, the speed of control WT (B, A) poor decaying at any time；
The corresponding weighting assessed value SW (B, A) of S2.5, TC (B, A) can calculate are as follows:
SW (B, A)=SC (B, A) * WT (B, A).
Preferably, in the step S3, trust the specific format for proving set are as follows:
TCs (A)={ TC (B1,A),TC(B2,A),...,TC(BNM(A),A)}
Wherein NM (A)≤η.
Preferably, the step S4 specific steps are as follows:
S4.1, it is potential interaction start when, the node C as Shi Xinzhe receives the credentials of the node A as receiver After bright set TCs (A), extracting trust therein first is proved, i.e. TC (B1,A)、TC(B2,A)、…、TC(BNM(A), A), if NM (A) < η, then the person C that applies letter to the trust value TV (C, A) of receiver A be set as constant, τ ∈ [0,1)；Otherwise, it applies letter person C passes through Trust the digital signature information in proving for every and verify its authenticity, then exporting every trust proves corresponding weighting assessed value And calculate TV (C, A)；Similarly, the person A that applies letter can be obtained to the trust value TV (A, C) of receiver C；
S4.2, when TV (C, A) >=TH (C) and TV (A, C) >=TH (A), node A is interacted with node C, Middle TH (C), TH (A) ∈ [0,1] are respectively the trust thresholding of node C, node A.
Preferably, in the step S4, applying letter, person C removes consideration time decaying weight WT (B, A) outside, it is also contemplated that interest is inclined Good similarity weight WS (C, B), the weight by the person C that applies letter and certifier B interest preference vector weighted euclidean distance DS (C, B it) exports, specific formula for calculation are as follows:
WS (C, B)=1-DS (C, B).
Further, in the step S4, the corresponding weighting assessed value ST (C, B, A) of TC (B, A) can be calculated are as follows:
ST (C, B, A)=SC (B, A) * WT (B, A) * WS (C, B)
Similarly, it applies letter person C can export TC (B1,A)、TC(B2,A)、…、TC(Bη, A) and corresponding weighting assessed value, and count Calculate the trust value TV (C, A) to receiver A, specific formula for calculation are as follows:
Compared with the prior art, the invention has the following advantages and beneficial effects:
1, the present invention uses complete Ad hoc mode, and the Three roles such as Shi Xinzhe, receiver, certifier are in different assessment ranks Duan Jinhang conversion, independent of trust center and roadside unit, thus more adapts to extensive, distributed car networking environment.
2, the present invention voluntarily stores and provides trust information by receiver, collects without Shi Xinzhe, it is thus possible to substantially Time, bandwidth consumption are reduced, realizes quick, lightweight trust evaluation.
Detailed description of the invention
Fig. 1 is the key step schematic diagram of the car networking method for evaluating trust embodiment of lightweight of the present invention.
Fig. 2 is the simplified example of the car networking method for evaluating trust embodiment of lightweight of the present invention.
Specific embodiment
Technical solution for a better understanding of the present invention, the implementation that the present invention is described in detail provides with reference to the accompanying drawing Example, embodiments of the present invention are not limited thereto.
Embodiment
As shown in Figs. 1-2, the present embodiment is free of trust center and roadside unit, and only by a large amount of ordinary nodes (i.e. vehicle) Composition, is communicated by wireless self-networking mode therebetween.The role of each node be Shi Xinzhe, receiver or certifier it One, and can be converted in different evaluation stages.
Step S1, at the end of node A, B is previously interacted, the B as certifier is the A as receiver according to interactive experience Generating a trust proves TC (B, A), specific format are as follows:
TC (B, A)=(ID (B), ID (A), RT (B, A), WG (B), TS (B, A), DS (B, A)) (1)
Wherein ID (B) and ID (A) respectively indicates the unique identifier of certifier B and receiver A；RT (B, A) indicates assessment It is worth vector, specific format are as follows:
RT (B, A)=(RT (B, A, 1), RT (B, A, 2) ..., RT (B, A, n)) (2)
Wherein n indicates to trust the number of aspect, and RT (B, A, i) (i ∈ [1, n]) indicates certifier B to the i-th of receiver A Assessed value in terms of a trust, value are represented as linguistic variable, as " very good ", " good ", " ", " poor ", " excessively poor " Deng；WG (B) indicates weighted value vector, specific format are as follows:
WG (B)=(WG (B, 1), WG (B, 2) ..., WG (B, n) (3)
Wherein WG (B, i) (i ∈ [1, n]) indicates that certifier B trusts i-th the interest preference level of aspect, value Be represented as linguistic variable, such as " very high ", "high", " in ", " low ", " very low "；TS (B, A) indicates that TC (B, A) is generated When timestamp；DS (B, A) indicates digital signature information.
Similarly, as the B of receiver be as certifier A generate TC (B, A) after send it to certifier A.It is similar Ground, it was demonstrated that person A is also that receiver B generates trust proof TC (A, B) and sends it to receiver B.
Step S2, it is that the trust itself generated proves to first verify that its signature after TC (B, A) that receiver A, which receives certifier B, Information DS (B, A) then judges the size relation of locally stored quantity NM (A) and η for trusting and proving, wherein η ∈ Z+To be System parameter: if NM (A) < η, receiver A directly store TC (B, A)；If NM (A)=η, receiver A calculate every credentials Bright corresponding weighting assessed value, and select accordingly and itself best η item trust proof is stored, while deleting other letters Appointing proves, the trust that receiver A is calculated is proved to trust including TC (B, A) and locally stored η item and be proved.
For calculating the corresponding weighting assessed value of TC (B, A): RT (B, A, i) can be by existing fuzzy letter in TC (B, A) Single additivity weight system [S.Y.Chou, Y.H.Chang, and C.Y.Shen, " A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes,"European Journal of Operational Research, 2008, vol.189, no.1, pp.132-145.] be converted to fuzzy evaluation RF (B, A, i) and clear assessment RC (B, A, i), the wherein specific calculating step of RF (B, A, i) are as follows:
RF (B, A, i)=(RF (B, A, i, 1), RF (B, A, i, 2), RF (B, A, i, 3), RF (B, A, i, 4)) (4)
Wherein, 0≤RF (B, A, i, 1)≤RF (B, A, i, 2)≤RF (B, A, i, 3)≤RF (B, A, i, 4)≤100；RC(B, A, i) be RF (B, A, i) symbolic distance, can specifically be exported by following formula:
Similarly, WG (B, i) can be exchanged into fuzzy weighted values WF (B, i) and clear weight WC (B, i), wherein WF (B, i) Specific format are as follows:
WF (B, i)=(WF (B, i, 1), WF (B, i, 2), WF (B, i, 3), WF (B, i, 4)) (6)
Wherein 0≤WF (B, i, 1)≤WF (B, i, 2)≤WF (B, i, 3)≤WF (B, i, 4)≤10；WC (B, i) can be by following Formula export:
Wherein, j, k are the temporary variable of summation.
Then, the corresponding fuzzy evaluation value SF (B, A) of TC (B, A) can calculate are as follows:
The corresponding clear assessed value SC (B, A) of TC (B, A) can calculate are as follows:
Receiver A only considers time decaying weight WT (B, A) when the most advantageous trust of selection proves, its calculation formula is:
Wherein TN indicates current time stamp；TS (B, A) is contained timestamp in TC (B, A)；ω indicates time window size； θ is time decay factor, the speed of control WT (B, A) poor decaying at any time.
Therefore, the corresponding weighting assessed value SW (B, A) of TC (B, A) can calculate are as follows:
SW (B, A)=SC (B, A) * WT (B, A) (11)
By formula (4)-(10) can be derived from RC (B, A, i) range be [0,100], and WC (B, i), WT (B, A), SC (B, A), the range of SW (B, A) is [0,1].
Similarly, receiver A, which calculates separately locally stored η item trust, proves corresponding weighting assessed value SW (B1,A)、 SW(B2,A)、…、SW(Bη, A), then from SW (B, A), SW (B1,A)、…、SW(Bη, A) in select η the larger value and store pair The trust answered proves, while deleting other and trusting proof.
Step S3, when potential interaction starts, receiver A desire is interacted with the node C as Shi Xinzhe, receiver A Taking out the trust being locally stored first proves, set is denoted as TCs (A), it may be assumed that
TCs (A)={ TC (B1,A),TC(B2,A),...,TC(BNM(A),A)}(12)
Wherein NM (A)≤η.Then, TCs (A) is sent to the person C that applies letter to prove that itself is believable by receiver A.
Similarly, TCs (C) is sent to the node A as Shi Xinzhe to prove that oneself is credible as the node C of receiver Rely.
Step S4, the trust that the person C that applies letter receives receiver A proves to pass through digital signature information first after set TCs (A) The authenticity proved is trusted in verifying, and extracting trust therein proves, i.e. TC (B1,A)、TC(B2,A)、…、TC(BNM(A), A), If NM (A) < η, the person C that applies letter to the trust value TV (C, A) of receiver A be set as lesser constant, τ ∈ [0,1)；Otherwise, it applies Letter person C trusts the digital signature information in proving by every and verifies its authenticity, and it is corresponding then to export every trust proof Weighting assessed value simultaneously calculates TV (C, A).
By taking the corresponding weighting assessed value ST (C, B, A) of the person C that applies letter export TC (B, A) as an example: the person C that applies letter is except the consideration time declines Subtract weight WT (B, A) (i.e. formula (10)) outside, it is also contemplated that interest preference similarity weight WS (C, B), the weight by the person C that applies letter with The weighted euclidean distance DS (C, B) of the interest preference vector of certifier B is exported, specific formula for calculation are as follows:
WS (C, B)=1-DS (C, B) (14)
Therefore, the corresponding weighting assessed value ST (C, B, A) of TC (B, A) can calculate are as follows:
ST (C, B, A)=SC (B, A) * WT (B, A) * WS (C, B) (15)
According to formula (13)-(15) the method, applying letter, person C can export TC (B1,A)、TC(B2,A)、…、TC(Bη,A) Corresponding weighting assessed value, and calculate the trust value TV (C, A) to receiver A, specific formula are as follows:
By formula (13)-(16) can be derived from WS (C, B), ST (C, B, A), TV (C, A) range be [0,1].
If TV (C, A) >=TH (C) (the wherein trust thresholding that TH (C) ∈ [0,1] is node C), then the person C that applies letter agree to by Letter person A interaction, vice versa.
Similarly, also set can be proved according to the trust that the node C as receiver is provided as the node A of Shi Xinzhe TCs (C) exports the trust value TV (A, C) to receiver C, and is according to the size relation decision for trusting thresholding TH (A) with itself No agreement is interacted with receiver C.
When TV (C, A) >=TH (C) and TV (A, C) >=TH (A), node A is interacted with node C.
The above embodiment is a preferred embodiment of the present invention, but embodiments of the present invention are not by above-described embodiment Limitation, other any changes, modifications, substitutions, combinations, simplifications made without departing from the spirit and principles of the present invention, It should be equivalent substitute mode, be included within the scope of the present invention.

Claims (9)

1.一种轻量级的车联网信任评估方法，其特征在于，具体包括如下步骤：1. a lightweight vehicle networking trust assessment method, is characterized in that, specifically comprises the following steps: S1、在节点先前交互结束时，交互双方均根据交互体验为对方生成一条包含自身数字签名的信任证明并发送给对方；S1. When the previous interaction between the nodes ends, both parties in the interaction generate a trust certificate containing their own digital signature for the other party according to the interaction experience and send it to the other party; S2、交互双方收到新的信任证明后验证其签名信息，并更新本地存储以保存对自身最有利的至多η条信任证明，其中η∈Z+为系统参数；S2. After receiving the new trust certificate, the two interacting parties verify their signature information, and update the local storage to save at most n trust certificates that are most beneficial to themselves, where η∈Z + is a system parameter; S3、在潜在交互开始时，潜在交互双方均将本地存储的信任证明发送给对方以证明自身可信赖；S3. At the beginning of the potential interaction, both parties of the potential interaction send the locally stored trust certificate to the other party to prove that they are trustworthy; S4、潜在交互双方通过数字签名信息验证信任证明的真实性并据此导出对方的信任值和决定是否同意与之交互，当且仅当双方都同意时进行交互。S4. Potentially interacting parties verify the authenticity of the trust certificate through the digital signature information, derive the trust value of the other party accordingly, and decide whether to agree to interact with it, if and only when both parties agree to interact. 2.根据权利要求1所述的轻量级的车联网信任评估方法，其特征在于，所述的步骤S1中，信任证明具体格式为：2. The lightweight IoV trust assessment method according to claim 1, wherein in the step S1, the specific format of the trust certificate is: TC(B，A)＝(ID(B)，ID(A)，RT(B，A)，WG(B)，TS(B，A)，DS(B，A))TC(B,A)=(ID(B), ID(A), RT(B,A), WG(B), TS(B,A), DS(B,A)) 其中B和A表示节点，B为证明者，A为受信者；ID(B)和ID(A)分别表示证明者B和受信者A的唯一标识符；RT(B，A)表示评估值向量，具体格式为：Among them, B and A represent nodes, B is the prover, and A is the trustee; ID(B) and ID(A) represent the unique identifiers of the prover B and trustee A, respectively; RT(B, A) represents the evaluation value vector , the specific format is: RT(B，A)＝(RT(B，A，1)，RT(B，A，2)，...，RT(B，A，n))RT(B, A) = (RT(B, A, 1), RT(B, A, 2), ..., RT(B, A, n)) 其中n表示信任方面的个数，RT(B，A，i)(i∈[1，n])表示证明者B对受信者A的第i个信任方面的评估值；WG(B)表示权重值向量，具体格式为：where n represents the number of trust aspects, RT(B, A, i) (i∈[1,n]) represents the evaluation value of the i-th trust aspect of the prover B to the trustee A; WG(B) represents the weight A vector of values, the specific format is: WG(B)＝(WG(B，1)，WG(B，2)，...，WG(B，n))WG(B)=(WG(B,1),WG(B,2),...,WG(B,n)) 其中WG(B，i)(i∈[1，n])表示证明者B对第i个信任方面的兴趣偏好水平；TS(B，A)表示TC(B，A)生成时的时间戳；DS(B，A)表示数字签名信息。where WG(B,i)(i∈[1,n]) represents the interest preference level of prover B for the i-th trust aspect; TS(B,A) represents the timestamp when TC(B,A) is generated; DS(B,A) represents digital signature information. 3.根据权利要求2所述的轻量级的车联网信任评估方法，其特征在于，所述RT(B，A，i)表示为语言变量，包括“非常好”、“好”、“一般”、“差”和“非常差”；所述WG(B，i)表示为语言变量，包括“非常高”、“高”、“中”、“低”和“非常低”。3. The lightweight IoV trust evaluation method according to claim 2, wherein the RT(B, A, i) is expressed as a language variable, including "very good", "good", "general" ", "poor", and "very poor"; the WG(B,i) is expressed as a linguistic variable, including "very high", "high", "medium", "low" and "very low". 4.根据权利要求1所述的轻量级的车联网信任评估方法，其特征在于，所述的步骤S2中，受信者A收到证明者B为自身生成的信任证明TC(B，A)后，首先验证其签名信息DS(B，A)，然后判断本地已存储信任证明的数量NM(A)与η的大小关系：若NM(A)＜η，则受信者A直接存储TC(B，A)；若NM(A)＝η，则受信者A计算每条信任证明对应的加权评估值，并据此选出对自身最有利的η条信任证明进行存储，同时删除其他信任证明，受信者A考虑的信任证明包括TC(B，A)和本地已存储的η条信任证明。4. The lightweight Internet of Vehicles trust evaluation method according to claim 1, wherein in the step S2, the trustee A receives the trust certificate TC (B, A) generated by the prover B for itself After that, first verify its signature information DS(B, A), and then judge the relationship between the number of locally stored trust certificates NM(A) and η: if NM(A) < η, the trustee A directly stores TC(B , A); if NM(A)=n, the trustee A calculates the weighted evaluation value corresponding to each trust certificate, and selects n trust certificates that are most beneficial to itself for storage, and deletes other trust certificates at the same time, The trust proofs considered by trustee A include TC(B, A) and n pieces of trust proofs that have been stored locally. 5.根据权利要求1所述的轻量级的车联网信任评估方法，其特征在于，所述步骤S2中，由TC(B，A)计算加权评估值的具体步骤为：5. The lightweight Internet of Vehicles trust evaluation method according to claim 1, wherein in the step S2, the specific steps of calculating the weighted evaluation value by TC (B, A) are: S2.1、将TC(B，A)中的RT(B，A，i)转换为模糊评估RF(B，A，i)和清晰评估RC(B，A，i)，其中RF(B，A，i)的具体格式为：S2.1. Convert RT(B,A,i) in TC(B,A) into fuzzy evaluation RF(B,A,i) and clear evaluation RC(B,A,i), where RF(B, The specific format of A, i) is: RF(B，A，i)＝(RF(B，A，i，1)，RF(B，A，i，2)，RF(B，A，i，3)，RF(B，A，i，4))RF(B,A,i)=(RF(B,A,i,1),RF(B,A,i,2),RF(B,A,i,3),RF(B,A,i , 4)) 其中0≤RF(B，A，i，1)≤RF(B，A，i，2)≤RF(B，A，i，3)≤RF(B，A，i，4)≤100；RC(B，A，i)为RF(B，A，i)的符号距离，具体可由以下公式导出：Where 0≤RF(B,A,i,1)≤RF(B,A,i,2)≤RF(B,A,i,3)≤RF(B,A,i,4)≤100; RC (B, A, i) is the signed distance of RF(B, A, i), which can be derived from the following formula: S2.2、将TC(B，A)中WG(B，i)转换为模糊权重WF(B，i)和清晰权重WC(B，i)，其中WF(B，i)的具体格式为：S2.2. Convert WG(B,i) in TC(B,A) into fuzzy weight WF(B,i) and sharp weight WC(B,i), where the specific format of WF(B,i) is: WF(B，i)＝(WF(B，i，1)，WF(B，i，2)，WF(B，i，3)，WF(B，i，4))WF(B, i) = (WF(B, i, 1), WF(B, i, 2), WF(B, i, 3), WF(B, i, 4)) 其中0≤WF(B，i，1)≤WF(B，i，2)≤WF(B，i，3)≤WF(B，i，4)≤10；WC(B，i)可由以下公式导出：where 0≤WF(B,i,1)≤WF(B,i,2)≤WF(B,i,3)≤WF(B,i,4)≤10; WC(B,i) can be calculated by the following formula Export: S2.3、TC(B，A)对应的模糊评估值SF(B，A)可计算为：The fuzzy evaluation value SF(B, A) corresponding to S2.3 and TC(B, A) can be calculated as: TC(B，A)对应的清晰评估值SC(B，A)可计算为：The clear evaluation value SC(B, A) corresponding to TC(B, A) can be calculated as: S2.4、受信者A在选择最有利信任证明时仅考虑时间衰减权重WT(B，A)，其计算公式为：S2.4. Trustee A only considers the time decay weight WT(B, A) when selecting the most favorable trust proof, and its calculation formula is: 其中，TN表示当前时间戳；TS(B，A)为TC(B，A)中所含时间戳；ω表示时间窗口大小；θ为时间衰减因子，控制WT(B，A)随时间差衰减的速度；Among them, TN represents the current timestamp; TS(B, A) is the timestamp contained in TC(B, A); ω represents the time window size; θ is the time decay factor, which controls the decay of WT(B, A) with the time difference speed; S2.5、TC(B，A)对应的加权评估值SW(B，A)可计算为：The weighted evaluation value SW(B, A) corresponding to S2.5 and TC(B, A) can be calculated as: SW(B，A)＝SC(B，A)*WT(B，A)。SW(B,A)=SC(B,A)*WT(B,A). 6.根据权利要求1所述的轻量级的车联网信任评估方法，其特征在于，所述的步骤S3中，信任证明集合的具体格式为：6. The lightweight IoV trust evaluation method according to claim 1, wherein in the step S3, the specific format of the trust certificate set is: TCs(A)＝{TC(B1，A)，TC(B2，A)，...，TC(BNM(A)，A)}TCs(A)={TC(B 1 ,A),TC(B 2 ,A),...,TC(B NM(A) ,A)} 其中NM(A)≤η。where NM(A)≤η. 7.根据权利要求1所述的轻量级的车联网信任评估方法，其特征在于，所述的步骤S4具体为：7. The lightweight IoV trust evaluation method according to claim 1, wherein the step S4 is specifically: S4.1、在潜在交互开始时，作为施信者的节点C收到作为受信者的节点A的信任证明集合TCs(A)后，首先提取出其中的信任证明，即TC(B1，A)、TC(B2，A)、...、TC(BNM(A)，A)，若NM(A)&lt;η，则施信者C对受信者A的信任值TV(C，A)被设为常数τ∈[0，1)；否则，施信者C通过每条信任证明中的数字签名信息验证其真实性，然后导出每条信任证明对应的加权评估值并计算TV(C，A)；同理，可得出施信者A对受信者C的信任值TV(A，C)；S4.1. At the beginning of the potential interaction, after receiving the trust certificate set TCs(A) of node A as the trustee, the node C, which is the trustee, first extracts the trust certificate, that is, TC(B 1 , A) , TC(B 2 , A), ..., TC(B NM(A) , A), if NM(A) &lt; is set as a constant τ∈[0, 1); otherwise, the trustor C verifies its authenticity through the digital signature information in each trust certificate, and then derives the weighted evaluation value corresponding to each trust certificate and calculates TV(C, A ); in the same way, the trust value TV(A, C) of the trustee A to the trustee C can be obtained; S4.2、当且仅当TV(C，A)≥TH(C)且TV(A，C)≥TH(A)时，节点A与节点C进行交互，其中TH(C)，TH(A)∈[0，1]分别为节点C、节点A的信任门限。S4.2. Node A interacts with node C if and only if TV(C, A) ≥ TH(C) and TV(A, C) ≥ TH(A), where TH(C), TH(A) )∈[0, 1] are the trust thresholds of node C and node A, respectively. 8.根据权利要求1所述的轻量级的车联网信任评估方法，其特征在于，所述的步骤S4中，施信者C除考虑时间衰减权重WT(B，A)外，还考虑兴趣偏好相似度权重WS(C，B)，该权重由施信者C与证明者B的兴趣偏好向量的加权欧式距离DS(C，B)导出，具体计算公式为：8 . The lightweight IoV trust evaluation method according to claim 1 , wherein in the step S4 , in addition to the time decay weight WT(B, A), the truster C also considers interest preferences. 9 . The similarity weight WS(C, B) is derived from the weighted Euclidean distance DS(C, B) of the interest preference vectors of the truster C and the prover B. The specific calculation formula is: WS(C，B)＝1-DS(C，B)。WS(C,B)=1-DS(C,B). 9.根据权利要求8所述的轻量级的车联网信任评估方法，其特征在于，所述的步骤S4中，TC(B，A)对应的加权评估值ST(C，B，A)可计算为：9. The lightweight IoV trust evaluation method according to claim 8, wherein in the step S4, the weighted evaluation value ST(C,B,A) corresponding to TC(B,A) can be Calculated as: ST(C，B，A)＝SC(B，A)*WT(B，A)*WS(C，B)ST(C,B,A)=SC(B,A)*WT(B,A)*WS(C,B) 同理，施信者C能够导出TC(B1，A)、TC(B2，A)、...、TC(Bη，A)对应的加权评估值，并计算对受信者A的信任值TV(C，A)，具体计算公式为：In the same way, the truster C can derive the weighted evaluation values corresponding to TC(B 1 , A), TC(B 2 , A), . . . , TC(B η , A), and calculate the trust value of the trustee A TV(C, A), the specific calculation formula is:
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