AU2018102186A4 - An aggregated trust evaluation method for message reliability in vanets - Google Patents
An aggregated trust evaluation method for message reliability in vanets Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/02—Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
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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
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
- H04L63/0442—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload wherein the sending and receiving network entities apply asymmetric encryption, i.e. different keys for encryption and decryption
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- 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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- 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
- H04L9/3263—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 certificates, e.g. public key certificate [PKC] or attribute certificate [AC]; Public key infrastructure [PKI] arrangements
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
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Abstract
In the present invention, an aggregated trust evaluation method for message
reliability in VANETs is disclosed. In the proposed method, the trust authority
is responsible for maintaining the trust information of vehicles. Vehicles
regularly request their latest trust certificates from the trust authority. Message
senders send messages with the latest trust certificates to prove their own
trustworthiness. After receiving each message, the message receiver extracts
the trust certificate and comprehensively considers the messages from multiple
message senders to decide whether they are reliable, then generates a trust
feedback for each message sender according to the quality of message and
sends it to the trust authority, which then updates the local storage. This
invention efficiently aggregates two kinds of trust evaluation, and does not
require message receivers to request the trust authority in real time, so the
evaluation is more accurate and the evaluation speed is faster. This invention is
compatible with the situation that vehicles cannot connect to the trust authority
in a short period, thus it is more suitable for the high dynamic characteristics in
VENETs.
1/1
RSU TA
S13
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FIG. 1
K-MR D DI
MDDMI
D
Note:
MRD: Maximum Recognition Distance;
MDD: Maximum Decision Distance;
MID: Maximum Influence Distance.
FIG. 2
Description
1/1
S13
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FIG. 1
Note: MRD: Maximum Recognition Distance; MDD: Maximum Decision Distance; MID: Maximum Influence Distance.
FIG. 2
The present invention generally relates to the field of security technology in Vehicular Ad hoc Networks (VANETs). More specifically, the invention relates to an aggregated trust evaluation method, which aggregates two kinds of trust evaluation methods (i.e. entity-oriented trust evaluation and data-oriented trust evaluation), for message reliability in VANETs.
As the main application of Internet of Things (IoTs) in the automobile industry and a core component of intelligent transportation system, VANETs play a vital role in urban road traffic for providing various information services, improving driving safety and efficiency, and promoting energy saving and emission reduction.
However, due to the large-scale, open, distributed, sparse and highly dynamic characteristics, VANETs are vulnerable to malicious behaviors and attacks. For example, malicious vehicles ("vehicle" is also known as "node" or "entity") may disseminate a large number of unreal messages ("message" is also known as "data" or "report") to deceive other nodes, thereby posing a great threat to the safety and reliability of road traffic. Therefore, each node needs to identify other honest nodes and malicious nodes, real and unreal messages, and make a correct decision according to the real messages issued by honest nodes.
Trust management plays a significant role in VANETs as it enables each node to evaluate the quality of messages from other nodes before acting on a message from other nodes for the purpose of avoiding the dire consequences caused by the unreal messages from malicious nodes. Currently, trust management in VANETs is still at the preliminary stage. According to the evaluation object, the existing trust evaluation methods can be roughly divided into entity-oriented trust evaluation and data-oriented trust evaluation.
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," in Proc. 2011 CNCC, 2011, pp. 436-441.] introduced a simple Long-Term Reputation (LTR) model in which roadside units monitor the daily behaviors of vehicles and maintain their trust information. However, the model considers each sender's message in isolation and completely ignores data-oriented trust, thus its actual performance is limited. Huang et al. [Z. Huang, S. Ruj, M. A. Cavenaghi, M. Stojmenovic, and A. Nayak, "A social network approach to trust management in VANETs," Peer Peer Netw. Appl., vol. 7, no. 3, pp. 229-242, Sep. 2014.] proposed a novel voting scheme from the social network perspective. In this scheme, each message receiver simultaneously considers the messages reporting a certain event and those reporting the opposite event so as to comprehensively decide the trustworthy of the event. However, this scheme totally ignores entity-oriented trust and gives the same weights to the messages of honest vehicles and those of malicious vehicles, so its actual performance is not good.
An objective of the present invention is to provide an aggregated trust evaluation method (which contains both entity-oriented trust evaluation and data-oriented trust evaluation) for message reliability in VANETs.
The objective of the present invention could be achieved by adopting the following technical solution:
An aggregated trust evaluation method for message reliability in VANETs
which comprises a Trust Authority (TA), a number of Road-Side Units (RSUs) and nodes (i.e. vehicles). The nodes and RSUs communicate with each other
through the relay of other nodes in a wireless way, while RSUs communicate
with the trust authority by wired medium. The trust authority is responsible for
maintaining the trust information and updating the trust value of each node at
the interval of At. For each node, the trust authority first selects the latest up to
rj trust feedbacks from other nodes to this node in the local storage, and then
calculates the new trust value of this node according to these feedbacks to
replace the old trust value. The trust evaluation method is as following:
Step SI: Each node requests its latest trust certificate from the trust
authority whenever it enters the communication range of a certain road-side
unit at the interval of At. After receiving the request information from a node
(e.g., S), the trust authority first verifies the request information really comes
from node S, and retrievals the latest trust value of this node from the local
storage, then generates a trust certificate for this node. Then the trust authority
sends the trust certificate to the node through the road-side unit and ensures the
confidentiality of the trust certificate by using asymmetric encryption. When
the node receives the trust certificate, it updates the local storage for later use
when sending new messages.
Step S2: When an event (e.g., E) takes place, the neighboring node can
witness it and broadcast this message to other nodes behind him as a message
sender. When a node (e.g., R, as a message receiver) receives a message that
reports an event E or its opposite event -E, it makes the decision according to
the distance DT(R, E) between node R and event E, Maximum Recognition
Distance (MRD), Maximum Decision Distance (MDD), and Maximum
Influence Distance (MID).
Step S3: When DT(R, E) is no larger than MRD, as a message receiver, node R can witness the actual state of event E and evaluate the quality of each message received previously, and then generate a trust feedback for each message sender. After entering the communication range of a certain road-side unit, message receiver R sends trust feedbacks to the trust authority. Then the trust authority verifies the signatures and updates the local storage.
Furthermore, the trust feedback is denoted as:
TF(A, S) = (ID(A), ID(S), TR(A, S), TS(A, S), DS(A, S)),
where ID(A) and ID(S) denote the unique identifiers of feedback-provider A and node S, respectively, TR(A, S) represents the evaluation score generated by feedback-provider A based on the previous message quality of node S, TS(A, S) represents the current timestamp, and DS(A, S) denotes the digital signature.
Furthermore, in step S2, node R's decision strategy according to DT(R, E), MRD, MDD, and MID is denoted as following:
S21: When DT(R, E) is larger than MID, node R directly discards the
messages reporting event E or its opposite event -E.
S22: When DT(R, E) is between MID and MDD, node R verifies the
digital signature in the received messages and stores the messages reporting
event E or its opposite event -E.
S23: When DT(R, E) is between MRD and MDD, node R makes a
comprehensive decision based on multiple messages reporting event E or its
opposite event -E received from different nodes.
S24: When DT(R, E) is no larger than MRD, node R can witness the real
state of event E and evaluate the quality of previous received messages.
Furthermore, the process in Step S23 that node R makes a comprehensive
decision based on multiple messages reporting event E or its opposite event -E
received from different nodes is as following:
1) TV(R, E) represents the comprehensive trust value of node R on event
E. If TV(R, E) > 0, as a message receiver, node R trusts event E and considers
that all the messages reporting event E are reliable and those reporting event -E
are unreliable. Meanwhile, node R acts on the messages reporting event E.
2) If TV(R, E) < 0, as a message receiver, node R trusts event -E and
consider all the messages reporting event -E are reliable and those reporting
event E are unreliable. Meanwhile, node R acts on the messages reporting event
3) If TV(R, E) = 0, as a message receiver, node R does not trust event E
or -E and considers all the messages reporting event E or -E are unreliable.
Meanwhile, node R does not take any action.
Furthermore, in Step S23, SS(E) = {S, S', . . Denotes message sender set,
where S and S' represent message senders, MS(S, E) and MS(S', E)
represent corresponding messages, and ISS(E)| denotes the number of
elements in SS(E). Event E and its opposite event -E are expressed as 1 and -1,
respectively. When calculating the comprehensive trust value TV(R,E) of event E, as a message receiver, node R considers the following weights:
1) Message Sender's Trust Value Weight Ws(R, S, E): The weight is
determined by message sender S's trust value TV(S) which is extracted from
the trust certificate. The calculation formula is as following:
Ws(R, S, E) = TV(S).
2) Trust Certificate's Time Decay Weight Wc(R, S, E): The weight
decreases exponentially with the time difference between the current timestamp
TN and the timestamp in the trust certificate. The calculation formula is as
following:
Wc(R, S, E) = e P ,
where p is a trust decay factor which controls the decay speed of
Wc(R, S, E) with the time difference.
3) Message's Time Decay Weight Wm(R, S, E): The weight decreases
exponentially with the time difference between the current timestamp TN and
the timestamp in the message. The calculation formula is as following:
TN-TS(S,E) Wm(R, S, E) = e ,
where T is a trust decay factor which controls the decay speed of
Wm(R, S, E) with the time difference.
The comprehensive trust value TV(R, E) is derived from the following formula:
TV(R, E) =SESS(E) ±1*Ws(R,S,E)*Wc(R,S,E)*Wm(R,S,E) ISS(E)|
TN-TS(TA,S) TN-TS(S,E) _ ASESS(E)±1*TV(S)*e P e ISS(E)|
Furthermore, when updating the trust value TV(S) of node S, the trust
authority considers the following weights:
1) Feedback-provider's Trust Value Weight Wf(A, S): It is determined by
the trust value of feedback-provider A. The calculation formula is as following:
Wf(A, S) = TV(A).
2) Time Decay Weight Wt(A, S): Wt(A, S) decreases exponentially with
the time difference between the current timestamp TN and the timestamp in
the trust feedback. The calculation formula is as following:
TN-TS(A,S) Wt(A, S) = e A
where A is a trust decay factor which controls the decay speed of Wt(A, S)
with the time difference.
The calculation formula of trust value TV(S) is denoted as following:
If the total number of trust feedbacks about node S is less than rl, the trust
value TV(S) is set to a small initial trust value, that is:
TV(S) = T E [0, 1].
Otherwise, the trust value TV(S) is derived from the following formula:
TV(S) - ZAEFS(S)TR(A,S)*Wf(A,S)*Wt(A,S) _ EAEFS(S)TR(A,S)*TV(A)*e 4*77 4*77
Furthermore, the format of request message sent by node S to the trust
authority is:
RQ(S, TA) = (ID(S), TS(S, TA), DS(S, TA)),
where ID(S) denotes the unique identifier of node S, TS(S,TA)
represents the timestamp when RQ(S,TA) is generated, DS(S,TA) denotes
the digital signature.
Furthermore, the format of trust certificate generated by the trust authority
for node S is:
TC(TA, S) = (ID(S), TV(S), TS(TA, S), DS(TA, S)),
where ID(S) denotes the unique identifier of node S, TV(S) represents
the trust value of node S, TS(TA, S) represents the timestamp when TC(TA, S)
is generated, DS(TA, S) denotes the digital signature.
Furthermore, TR(A, S) represents the evaluation score generated by
feedback-provider A based on the previous message quality of node S, and its
value is an integer between 0 and 4. Besides, the higher the quality of message
is, the larger the value is.
Compared with the prior art, the present invention provide several
advantages:
1) The present invention efficiently aggregates two kinds of trust
evaluation and comprehensively considers multiple messages reporting an
event or its opposite event received from different nodes to evaluate the
reliability of messages, thus significantly improves the evaluation accuracy.
2) The present invention does not require message receivers to request the
trust authority in real time, thus the evaluation speed is faster.
3) The present invention is compatible with the situation that vehicles
cannot connect to the trust authority in a short period, thus it is more suitable
for the highly dynamic characteristics in VENETs.
FIG. 1 is a schematic diagram of main steps in the technical solution of the
present invention.
FIG. 2 is a schematic diagram of three kinds of distances in the technical
solution of the present invention.
Embodiment
Before embodiments of the present invention are mentioned, it is to be
understood that the present invention is not limited to the particular methods aforementioned, as these may vary. It is also to be understood that the terminology used in the description is only for the purpose of describing the particular versions or embodiments, and is not intended to limit the scope of the invention.
The detailed description of the technical solution is showed below combined with figure 1 and figure 2.
The preferred embodiment of the present invention includes three elements, namely, Trust Authority (TA), Road-Side Units (RSUs) and vehicles (i.e. nodes), wherein, the nodes and RSUs communicate with each other through the relay of other nodes in a wireless way, while RSUs communicate with the trust authority by wired medium.
The trust authority is responsible for maintaining the trust information and updating the trust value of each node at the interval of At.
In an embodiment, for example, when calculating the trust value TV(S) of node S, the trust authority first selects the latest up to rj trust feedbacks (i.e., TF(A, S) , TF(B, S) , TF(C, S) ) from other nodes (e.g., A, B, C, as feedback-providers) to this node in the local storage and then adds the responding nodes to the feedback-provider set FS(S) (i.e., FS(S)= {A, B, C, . . }).
The format of trust feedback is:
TF(A, S) = (ID(A), ID(S), TR(A, S), TS(A, S), DS(A, S)), (1)
where ID(A) and ID(S) denote the unique identifiers of
feedback-provider A and node S, respectively, TR(A, S) represents the
evaluation score (i.e. an integer between 0 and 4, and the higher the quality of message is, the larger the evaluation score is) generated by feedback-provider A based on the previous message quality of node S, TS(A, S) represents the current timestamp, DS(A, S) denotes the digital signature. The format of
TF(B, S), TF(C, S) and other trust feedbacks are consistent with that of
When updating the trust value TV(S) of node S, the trust authority
considers the following weights:
1) Feedback-provider's Trust Value Weight Wf(A, S): It is determined by
the trust value of feedback-provider A. The calculation formula is as following:
Wf(A, S) = TV(A). (2)
2) Time Decay Weight Wt(A, S): Wt(A, S) decreases exponentially with
the time difference between the current timestamp TN and the timestamp in
the trust feedback. The calculation formula is as following:
TN-TS(A,S) Wt(A, S) = e A (3)
where A is a trust decay factor which controls the decay speed of Wt(A, S)
with the time difference.
If the total number of trust feedbacks on node S is less than rj, the trust
value TV(S) is set to a small initial trust value, that is:
TV(S) = T E [0, 1]. (4)
Otherwise, the trust value TV(S) is derived from the following formula:
TV(S)- AAEFS(S)TR(A,S)*Wf(A,S)*Wt(A,S) _ ZAEFS(S)TR(A,S)*TV(A)*e (5) 4*77 4*77
From formula (2) - (5), we can know that the ranges of Wf(A, S),
Wt(A, S), TV(S) are all [0, 1]. After calculating TV(S), the trust authority
uses it to replace the trust value of node S previously stored.
Step 1: Each node requests its latest trust certificate from the trust
authority whenever it enters the communication range of a certain RSU at an
interval of At. Take node S as an example, the format of the request message
sent by node S to the trust authority is:
RQ(S, TA) = (ID(S), TS(S, TA), DS(S, TA)), (6)
where ID(S) denotes the unique identifier of node S, TS(S, TA) represents
the timestamp when RQ(S,TA) is generated, DS(S,TA) denotes the digital
signature.
After receiving the request information from node S, the trust authority first verifies the request information really comes from node S by DS(S, TA), and retrieves the latest trust value of this node from the local storage, then generates a trust certificate for this node. The format of the trust certificate is as following:
TC(TA, S) = (ID(S), TV(S), TS(TA, S), DS(TA, S)), (7)
where ID(S) denotes the unique identifier of node S, TV(S) represents the trust value of node S, TS(TA, S) represents the timestamp when TC(TA, S) is generated, DS(TA, S) denotes the digital signature.
Subsequently, the trust authority sends the trust certificate to node S
through the RSU and ensures the confidentiality of the trust certificate by using
asymmetric encryption. When node S receives the trust certificate, it updates
the local storage for later use when sending new messages.
Step S2: When an event E (e.g., icy road) takes place, a neighboring node
(e.g., node S) can witness it and broadcast this event to other nodes behind him
as a message sender. Node S is called a witness and is also named a message
sender. The format of node S's message is:
MS(S, E) = (ID(S), MC(S, E), TC(TA, S), TS(S, E), DS(S, E)), (8)
where ID(S) denotes the unique identifier of node S, MC(S, E) represents
the message content, TC(TA, S) represents the trust certificate of node S,
TS(S, E) represents the timestamp when MS(S, E) is generated, DS(S, E)
denotes the digital signature.
In practice, when an event E occurs, multiple nodes (e.g., node S, node S',
etc.) may witness it and report it to other nodes behind them, where there may
exist some malicious nodes that report the opposite event -E (e.g., road clear) to
deceive other nodes. Therefore, when a node evaluates the reliability of event E,
it should comprehensively consider multiple messages reporting an event E or
its opposite event -E received from different nodes to improve the accuracy of
evaluation.
When a node (e.g., node R, as a message receiver) receives a message that
reports an event E or its opposite event -E, it makes the decision according to
the distance DT(R, E) between node R and event E, Maximum Recognition
Distance (MRD), Maximum Decision Distance (MDD), and Maximum
Influence Distance (MID).
As depicted in FIG. 2, there are three kinds of distances (i.e., MRD, MDD,
and MID) in the vicinity of an event E.
1) When DT(R, E) is larger than MID, node R directly discards the
messages reporting event E or its opposite event -E.
2) When DT(R, E) is between MID and MDD, node R verifies the digital
signature in the received messages and stores the messages reporting event E or
its opposite event -E.
3) When DT(R, E) is between MRD and MDD, node R makes a
comprehensive decision based on multiple messages reporting event E or its
opposite event -E received from different nodes.
4) When DT(R, E) is no larger than MRD, node R can witness the real
state of event E and evaluate the quality of previous received messages.
In the above case 3), SS(E) = {S, S', . . Denotes message sender set,
where node S and node S' represent message senders, MS(S, E) and
MS(S',E) represent corresponding messages, and ISS(E)| denotes the number of elements in SS(E). Event E and its opposite event -E are expressed as 1 and
-1, respectively.
When calculating the comprehensive trust value of event E, message
receiver R considers the following weights:
1) Message Sender's Trust Value Weight Ws(R, S, E): The weight is
determined by message sender S's trust value TV(S) which is extracted from
the trust certificate. The calculation formula is as following:
Ws(R, S, E) = TV(S). (9)
2) Trust Certificate's Time Decay Weight Wc(R, S, E): The weight
decreases exponentially with the time difference between the current timestamp
TN and the timestamp in the trust certificate. The calculation formula is as
following:
Wc(R, S, E) = e P (10)
where p is a trust decay factor which controls the decay speed of
Wc(R, S, E) with the time difference.
3) Message's Time Decay Weight Wm(R, S, E): The weight decreases
exponentially with the time difference between the current timestamp TN and
the timestamp in the message. The calculation formula is as following:
TN-TS(S,E) Wm(R, S, E) = e P (11) where $ is a trust decay factor which controls the decay speed of
Wm(R, S, E) with the time difference.
The comprehensive trust value TV(R, E) is derived from the following
formula:
TV(R, E) = ASESS(E) ±1*Ws(R,S,E)*Wc(R,S,E)*Wm(R,S,E) ISS(E)|
TN-TS(TA,S) TN-TS(S,E) _ ASESS(E)±1*TV(S)*e I P *e |SS(E)|(12
From formula (9) - (12), we can find that the ranges of Ws(R, S, E),
Wc(R, S, E), Wm(R, S, E) are [0, 1], while the range of TV(R, E) is [-1, 1].
1) TV(R, E) represents the comprehensive trust value of node R on event
E. If TV(R, E) > 0, node R trusts event E and considers that all the messages
reporting event E are reliable and those reporting event -E are unreliable, and
then node R acts on the messages reporting event E.
2) If TV(R, E) < 0, node R trusts event -E and consider all the messages
reporting event -E are reliable and those reporting event E are unreliable. Then
node R acts on the messages reporting event -E.
3) If TV(R, E) = 0, node R does not trust event E or -E and considers all
the messages reporting event E or -E are unreliable. Meanwhile, node R does
not take any action.
Step S3: When DT(R, E) is no larger than MRD, node R can witness the
actual state of event E and evaluate the quality of each message received previously, and then generates a trust feedback in the format shown in (1) for each message sender. After entering the communication range of a certain RSU, message receiver R sends these generated trust feedbacks to the trust authority. Then the trust authority verifies the signatures of node R and updates the local storage.
It is to be understood that the invention is not limited in its application to the details of construction and to the arrangements of the components set forth in this description or illustrated in the drawings. The disclosed methods are capable of other embodiments and of being practiced and carried out in various ways. Hence, it is to be understood that the phraseology and terminology employed herein are for the purpose of description and should not be regarded as limiting.
Claims (9)
1. An aggregated trust evaluation method for message reliability in VANETs
which comprises a Trust Authority (TA), a number of Road-Side Units (RSUs)
and nodes. The nodes and RSUscommunicate with each other through the relay
of other nodes in a wireless way, while RSUs communicate with the trust
authority by wired medium. The trust authority is responsible for maintaining
the trust information and updating the trust value of each node at the interval of
At. For each node, the trust authority first selects the latest up to rj trust
feedbacks from other nodes to this node in the local storage, and then calculates
the new trust value of this node according to these feedbacks to replace the old
trust value. The trust evaluation method is as following:
Step Sl: Each node requests its latest trust certificate from the trust
authority whenever it enters the communication range of a certain road-side
unit at the interval of At. After receiving the request information from a node S,
the trust authority first verifies the request information really comes from node
S, and retrievals the latest trust value of this node from the local storage, then generates a trust certificate for this node. Then the trust authority sends the trust
certificate to the node through the road-side unit and ensures the confidentiality
of the trust certificate by using asymmetric encryption. When the node receives
the trust certificate, it updates the local storage for later use when sending new
messages.
Step S2: When an event E takes place, the neighboring node can witness it
and broadcast this message to other nodes behind him as a message sender.
When a node R, as a message receiver, receives a message that reports an event
E or its opposite event -E, it makes the decision according to the distance
DT(R,E) between node R and event E, Maximum Recognition Distance
Maximum Decision Distance, and Maximum Influence Distance.
Step S3: When DT(R, E) is no larger than MRD, node R can witness the
actual state of event E and evaluate the quality of each message received
previously, and then generate a trust feedback for each message sender. After
entering the communication range of a certain road-side unit, message receiver
R sends these generated trust feedbacks to the trust authority. Then the trust
authority verifies the signatures of message receiver R and updates the local
storage.
2. An aggregated trust evaluation method for message reliability in
VANETs of claim 1, wherein the format of trust feedback is:
TF(A, S) = (ID(A), ID(S), TR(A, S), TS(A, S), DS(A, S)),
where ID(A) and ID(S) denote the unique identifiers of
feedback-provider A and node S, respectively, TR(A, S) represents the
evaluation score generated by feedback-provider A based on the previous
message quality of node S, TS(A, S) represents the current timestamp, DS(A, S) denotes the digital signature.
3. An aggregated trust evaluation method for message reliability in
VANETs of claim 1, wherein node R's decision strategy according to DT(R, E),
MRD, MDD, and MID is denoted as following:
S21: When DT(R, E) is larger than MID, node R directly discards the
messages reporting event E or its opposite event -E.
S22: When DT(R, E) is between MID and MDD, node R verifies the digital signature in the received messages and stores the messages reporting event E or its opposite event -E.
S23: When DT(R, E) is between MRD and MDD, node R makes a
comprehensive decision based on multiple messages reporting event E or its
opposite event -E received from different nodes.
S24: When DT(R, E) is no larger than MRD, node R can witness the real
state of event E and evaluate the quality of previous received messages.
4. An aggregated trust evaluation method for message reliability in
VANETs of claim 1, wherein the process aforementioned in step S23 that node
R makes a comprehensive decision based on multiple messages reporting event
E or its opposite event -E received from different nodes is as following:
1) TV(R, E) represents the comprehensive trust value of node R on event
E. If TV(R, E) > 0, as a message receiver, node R trusts event E and considers
that all the messages reporting event E are reliable and those reporting event -E
are unreliable, and then node R acts on the messages reporting event E.
2) If TV(R, E) < 0, as a message receiver, node R trusts event -E and
consider all the messages reporting event -E are reliable and those reporting
event E are unreliable. Then node R acts on the messages reporting event -E.
3) If TV(R, E) = 0, as a message receiver, node R does not trust event E
or -E and considers all the messages reporting event E or -E are unreliable.
Meanwhile, node R does not take any action.
5. An aggregated trust evaluation method for message reliability in
VANETs of claim 1, wherein in step S23, SS(E) = {S, S', . . Denotes message
sender set, where S and S' represent message senders, MS(S, E) and
MS(S',E) represent corresponding messages, and ISS(E)| denotes the number
of elements in SS(E). Event E and its opposite event -E are expressed as 1 and
-1, respectively. When calculating the comprehensive trust value TV(R, E) of
event E, as a message receiver, node R considers the following weights:
1) Message Sender's Trust Value Weight Ws(R, S, E): It is determined by
message sender S's trust value TV(S) which is extracted from the trust
certificate. The calculation formula is as following:
Ws(R, S, E) = TV(S),
2) Trust Certificate's Time Decay Weight Wc(R, S, E): The weight
decreases exponentially with the time difference between the current timestamp
TN and the timestamp in the trust certificate. The calculation formula is as
following:
TN-TS(TA,S) Wc(R, S, E) = e 'P
where p is a trust decay factor which controls the decay speed of
Wc(R, S, E) with the time difference.
3) Message's Time Decay Weight Wm(R, S, E): The weight decreases exponentially with the time difference between the current timestamp TN and the timestamp in the message. The calculation formula is as following:
TN-TS(S,E) Wm(R, S, E) = e
, where $ is a trust decay factor which controls the decay speed of
Wm(R, S, E) with the time difference.
The comprehensive trust value TV(R, E) is derived from the following
formula:
TV(R, E) =SESS(E) ±1*Ws(R,S,E)*WC(R,S,E)*WM (R,S,E) ISS(E)|
TN-TS(TA,S) TN-TS(S,E) _ ESESS(E)±1*TV(S)*e P e ISS(E)|
6. An aggregated trust evaluation method for message reliability in
VANETs of claim 1, wherein when updating the trust value TV(S) of node S,
the trust authority considers the following weights:
1) Feedback-provider's Trust Value Weight Wf(A, S): It is determined by
the trust value of feedback-provider A. The calculation formula is as following:
Wf(A, S) = TV(A),
2) Time Decay Weight Wt(A, S): Wt(A, S) decreases exponentially with
the time difference between the current timestamp TN and the timestamp in
the trust feedback. The calculation formula is as following:
TN-TS(A,S) Wt(A, S) = e A
where A is a trust decay factor which controls the decay speed of Wt(A, S)
with the time difference.
The calculation formula of aforementioned trust value TV(S) is denoted
as following:
If the total number of trust feedbacks about node S is less than rj, the trust
value TV(S) is set to a small initial trust value, that is:
TV(S) = T E [0, 1].
Otherwise, the trust value TV(S) is derived from the following formula:
TN-TS(A,S)
TV(S)TVS)=4*77 - AAEFS(S) TR(A,S)*Wf(A,S)*Wt(A,S)__ EAEFS(S)TR(A,S)*TV(A)*e 4*77
7. An aggregated trust evaluation method for message reliability in
VANETs of claim 1, wherein the format of request message sent by node S to
the trust authority is:
RQ(S, TA) = (ID(S), TS(S, TA), DS(S, TA)),
where ID(S) denotes the unique identifier of node S, TS(S,TA)
represents the timestamp when RQ(S,TA) is generated, DS(S,TA) denotes
the digital signature.
8. An aggregated trust evaluation method for message reliability in
VANETs of claim 1, wherein the format of trust certificate generated by the trust authority for node S is:
TC(TA, S) = (ID(S), TV(S), TS(TA, S), DS(TA, S)),
where ID(S) denotes the unique identifier of node S, TV(S) represents
the trust value of node S, TS(TA, S) represents the timestamp when TC(TA, S)
is generated, DS(TA, S) denotes the digital signature.
9. An aggregated trust evaluation method for message reliability in
VANETs of claim 1, wherein TR(A, S) represents the evaluation score
generated by feedback-provider A based on the previous message quality of
node S, and its value is an integer between 0 and 4. Besides, the higher the
quality of message is, the larger the value is.
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| CN201811190159.9 | 2018-10-12 | ||
| CN201811190159.9A CN109195162B (en) | 2018-10-12 | 2018-10-12 | Message reliability assessment method for aggregating two kinds of trust assessment in Internet of vehicles |
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| CN110418309B (en) * | 2019-07-30 | 2022-06-28 | 深圳成谷科技有限公司 | Method, device and equipment for issuing vehicle-road cooperative certificate and vehicle-mounted unit |
| CN112399347B (en) * | 2019-07-31 | 2022-04-05 | 华为技术有限公司 | Message processing method and device |
| CN110445788B (en) * | 2019-08-09 | 2021-07-27 | 西安电子科技大学 | Content-oriented trust evaluation system and method under vehicle-mounted ad hoc network environment |
| CN110446204B (en) * | 2019-09-11 | 2022-10-04 | 南通大学 | Trust value calculation method suitable for Internet of vehicles network vehicle node |
| CN110809253B (en) * | 2019-11-11 | 2023-03-24 | 上海第二工业大学 | Certificateless aggregate signature method for vehicle-mounted ad hoc network |
| CN111507564B (en) * | 2020-03-09 | 2022-04-29 | 浙江大学 | Urban road alarm message reliability assessment method integrating space-time correlation |
| CN111885539B (en) * | 2020-07-23 | 2023-10-10 | 杭州师范大学 | Internet of vehicles vehicle reputation updating method based on dynamic adjustment of updating interval |
| CN114945149A (en) * | 2021-02-10 | 2022-08-26 | 普天信息技术有限公司 | V2X node message credibility assessment method and device based on reputation |
| CN113380024B (en) * | 2021-05-27 | 2022-09-02 | 重庆邮电大学 | Reputation updating method and trust calculation method based on Internet of vehicles |
| CN115002002B (en) * | 2022-04-02 | 2024-02-13 | 中国兵器科学研究院 | Equipment system information communication capability assessment method, device, equipment and medium |
| CN115174615B (en) * | 2022-06-27 | 2024-04-19 | 武汉大学 | Distributed Internet of vehicles dynamic trust management method based on origin information |
| CN115473820B (en) * | 2022-08-09 | 2024-05-28 | 武汉大学 | Event-driven social networking malicious behavior detection method and system |
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| CN101404591B (en) * | 2008-11-14 | 2010-11-10 | 西安交通大学 | Self-adapting dynamic trust weight estimation method |
| US8923147B2 (en) * | 2011-10-03 | 2014-12-30 | Qualcomm Incorporated | Method and apparatus for filtering and processing received vehicle peer transmissions based on reliability information |
| CN103957525B (en) * | 2014-05-12 | 2018-02-27 | 江苏大学 | Malicious node detection method based on sub-clustering trust evaluation in car networking |
| CN104333596B (en) * | 2014-11-11 | 2017-06-16 | 安徽大学 | Information reliability assessment method in Internet of vehicles environment |
| CN104732237B (en) * | 2015-03-23 | 2017-10-27 | 江苏大学 | The recognition methods of false transport information in a kind of car networking |
| KR101736007B1 (en) * | 2015-09-16 | 2017-05-15 | 한양대학교 에리카산학협력단 | Method and apparatus for verifying location and time of in-vehicle dashcam videos under owners' anonymity |
| CN105430638B (en) * | 2015-10-22 | 2018-12-28 | 重庆邮电大学 | A kind of data safety retransmission method with the perception of public key trust degree |
| CN106953839B (en) * | 2017-01-13 | 2020-06-16 | 重庆邮电大学 | System and method for controlling propagation of untrusted resources in Internet of vehicles |
| CN107835077B (en) * | 2017-09-22 | 2020-10-02 | 中国人民解放军国防科技大学 | Mutual trust cluster collaborative verification method for anonymous authentication of vehicle-mounted network |
| CN108053665B (en) * | 2018-01-15 | 2019-05-03 | 长安大学 | The traffic information of double faith mechanisms identifies retransmission method in car networking environment |
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