LoWVR: Low Overhead Watermark based Vehicle Revocation Scheme in VANET

Author(s):  
Atanu Mondal ◽  
Sulata Mitra

Background and Objective: The inter-vehicle communication is a potential issue for improving road safety, detecting traffic accidents, etc. in vehicular ad hoc network. The communication among the vehicles in VANET must be protected from the dissemination of message by unauthorized vehicles and the alteration of the message by misbehaving vehicles. Methods: In this paper, a low overhead digital watermark based vehicle revocation scheme is proposed. The sender vehicle generates a message and a random number after observing an event. It generates a deformed version of the generated message and message digest, and concatenates them. The watermark bits are generated by the sender vehicle from its unique identification and the random number. The sender vehicle embeds the watermark bits in the concatenated form of the message digest and deformed version of the generated message, and broadcasts the embedded message for its neighbours. The neighbour vehicles extract the required information from the received embedded message to verify the authentication of the sender vehicle and to identify whether the sender vehicle is an alteration attacker. It revokes unauthentic vehicles and vehicles that are identified as alteration attacker from vehicular ad-hoc network without any dependency on the trusted third party. The cracking probability and cracking time are used to measure the robustness of the scheme. The cracking probability and cracking time are measured to set the design guideline regarding the size of the watermark. The qualitative performance of the scheme is measured in terms of storage, communication and computation overhead. The significant reduction of all such overheads is observed by comparing the qualitative performance of the proposed scheme with two existing schemes. Conclusion and Results: Thus, the proposed scheme is a low overhead solution of securing vehicular ad hoc network. Performance of the scheme is also studied quantitatively in terms of the time of verifying vehicle authentication at the receiving end, delay in message dissemination at the sending end and delay in message reception at the receiving end. The quantitative performance is also compared with two of the existing schemes.

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Lishui Chen ◽  
Jing Wang ◽  
Xing Chen ◽  
Yifu Zhang

Effective message forwarding between vehicles can reduce the occurrence of traffic accidents and improve the driving experience. Vehicle clustering can improve message utilization, but attackers in the network pose a serious threat to message forwarding. Based on vehicle clustering, we propose a message forwarding strategy for Vehicular Ad hoc Network. Specifically, the vehicles are clustered based on their directions and speeds. Besides, the friendship of vehicles is evaluated in terms of the interaction friendship and reference friendship. Based on the friendship of vehicles, the optimal vehicle can be selected as the cluster head. Thereafter, the double key technology is designed to encrypt vehicular messages such that the messages can be forwarded more safely and efficiently. The analysis results show that the proposed strategy can effectively improve the message delivery rate, reduce the message leakage rate, and improve the network performance.


2017 ◽  
Vol 13 (8) ◽  
pp. 155014771772569 ◽  
Author(s):  
Liang Pang ◽  
Xiao Chen ◽  
Yong Shi ◽  
Zhi Xue ◽  
Rida Khatoun

In vehicular ad hoc network, wireless jamming attacks are easy to be launched in the control channel and can cause serious influence on the network performance which may cause further safety accidents. In order to address the issue of wireless jamming attacks, a new technique which localizes the jamming attackers and prevents vehicles from jamming through human intervention is proposed. In this article, we propose a range-free approach to localize the source of the attacker and determine the number of jamming attackers. The data set is the locating information and the jamming detection information associated with each vehicle. Then, we formulate the problem of determining the number of attackers as a multiclass detection problem. We define the incorrectly classified area and use it to measure the distance between samples and centroids in fuzzy c-means algorithm. We further determine the number of jamming attackers through the coverage rate of beaconing circles and utilize weight-based fuzzy c-means to classify the data set. When the data set is classified as acceptable, we further explore the means of using particle swarm optimization algorithm to calculate the positional coordinates of each attacker. We simulate our techniques in MATLAB, and both urban traffic area and open area are considered in our simulation. The experimental results suggest that the proposed algorithm can achieve high precision when determining the number of attackers while the result of the classified performance is always satisfying. Our localization results lead to higher accuracy than other existing solutions. Also, when the data set is limited, the chances of taking accurate localization are higher than other measures.


2017 ◽  
Vol 13 (12) ◽  
pp. 155014771774369 ◽  
Author(s):  
Xiaoliang Wang ◽  
Shuifan Li ◽  
Shujing Zhao ◽  
Zhihua Xia ◽  
Liang Bai

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