ARV2V: Attack resistant vehicle to vehicle algorithm, performance in term of end-to-end delay and trust computation error in VANETs

Rehman, Mujeeb Ur; Ahmed, Sheeraz; Khan, Shahbaz; Begum, Shabana; Ishtiaq, Atif

doi:10.1109/icomet.2018.8346338

Cited by 5 publications

(2 citation statements)

References 15 publications

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“…They have defined existing routing protocols and classified it in proactive (table-driven) and reactive (on-demand) mode. An attack resistant based vehicle to vehicle algorithm has been proposed in [14] which provides better performance than the existing schemes. They analyzed end to end delay (EED) and trust computation error (TCE) in trust in scheme ARV2V.…”

Section: Related Workmentioning

confidence: 99%

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Malicious vehicle detection based on beta reputation and trust management for secure communication in smart automotive cars network

Hossain

Reza

2021

TELKOMNIKA

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High reliance on wireless network connectivity makes the vehicular ad hoc network (VANET) vulnerable to several kinds of cyber security threats. Malicious vehicles accessing the network can lead to hazardous situation by disseminating misleading information or data in the network or by performing cyber-attacks. It is a requirement that the information must be originated from the authentic and authorized vehicle and confidentiality must be maintained. In these circumstances, to protect the network from malicious vehicles, reputation system based on beta probability distribution with trust management model has been proposed to differentiate trustworthy vehicles from malicious vehicles. The trust model is based on adaptive neuro fuzzy inference system (ANFIS) which takes trust metrics as input to evaluate the trustworthiness of the vehicles. The simulation platform for the model is in MATLAB. Simulation results show that the vehicles need at least 80% trustworthiness to be considered as a trusted vehicle in the network.

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Section: Related Workmentioning

confidence: 99%

“…These nodes perform normalize operation on the output of the layer 2. Normalization operation can be represented as (14),…”

Section: Anfismentioning

confidence: 99%

Malicious vehicle detection based on beta reputation and trust management for secure communication in smart automotive cars network

Hossain

Reza

2021

TELKOMNIKA

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Communication by Credence: Trust Communication in Vehicular Ad Hoc Networks

2021

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MAR_Sybil: Cooperative RSU Based Detection and Prevention of Sybil Attacks in Routing Process of VANET

Kabbur

Kumar

2020

J. Phys.: Conf. Ser.

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VANET is a next generation communication technology where vehicles create an autonomous network with assistance of RSU (Road Side Units). VANET provides legitimate information to the users on the road, in order to increase the road and user’s safety. It provides useful information to the vehicles about directions, location mapping, premises, etc. The fast propagation of emergency and local warning messages to the approaching vehicles will be helpful for preventing secondary accidents. If security of the network is not guaranteed, several attacks may occur, thereby alert messages may not reach to the RSUs on time or message may get spoof due to attack on it. Major attacks on emergency messages such as timing attack, spoofing attack, DoS attack, Sybil attack, etc. would be considered to mitigate and make the communication and infrastructure more secure. One of the major emergency message attack is Sybil, which is used by selfish message propagators to claim authenticity of their message by propagating with multiple identities. By deceiving other nodes with their false support using multiple identifies, they can achieve various purpose in network like vehicle re-routing, speed shift etc. This work proposes a RSU cooperative detection mechanism involving triangulation and fake propagation by RSU to identify the Sybil attacks in the VANET. The proposed methodology secures fast communication emergency messages to prevent secondary accidents by validating the message sources, nodes will accept only the messages from RSU which are digitally signed and source validated against Sybil nodes. The performance evaluation is made with existing methodology and effectiveness of the proposed methodology results demonstrated in article. The spatial location and trajectory of attacker is learnt effectively with RSU cooperation in the proposed work.

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ARV2V: Attack resistant vehicle to vehicle algorithm, performance in term of end-to-end delay and trust computation error in VANETs

Cited by 5 publications

References 15 publications

Malicious vehicle detection based on beta reputation and trust management for secure communication in smart automotive cars network

Malicious vehicle detection based on beta reputation and trust management for secure communication in smart automotive cars network

Communication by Credence: Trust Communication in Vehicular Ad Hoc Networks

MAR_Sybil: Cooperative RSU Based Detection and Prevention of Sybil Attacks in Routing Process of VANET

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