TACR: Trust Aware Clustering-Based Routing for Secure and Reliable VANET Communications

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作者
Megha V. Kadam
Vinod M. Vaze
Satish R. Todmal
机构
[1] Shri. JJT University,
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关键词
Access control; Ant colony optimization; Clustering; Fuzzy logic; Routing; Vehicular ad hoc network;
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摘要
Achieving security and privacy preservation considering the network dynamics and overhead is a vital research problem. Long-distance communications in highly dynamic VANET have been effectively supported by using the appropriate clustering algorithms. However, stable clustering with minimum overhead is a vital requirement for VANET QoS improvement. On another side, an access control mechanism for data security and privacy preservation becomes essential in such sensitive networks to prevent harmful activities. The cryptography-based access control techniques lead to higher delay and overhead in the network, therefore need a lightweight routing mechanism to define the access control policies in the network. We propose the novel Trust Aware Clustering-based Routing Protocol (TACR) to address the challenges related to security and reliability in VANET communications with minimum computational costs and delay. As the name indicates, the TACR functionality depends on effective trust-management strategies for optimal Cluster Head (CH) selection and optimal relay (data forwarder) selection. In the clustering phase, we compute the direct and indirect trust scores of each vehicle belonging to each cluster. We use the hybrid trust value of each vehicle as an outcome of the fitness function in the Ant Colony Optimization (ACO) algorithm. The ACO algorithm performs the evaluation and selection of stable vehicles for optimal CH. In the routing phase, we formulate the problem of secure and reliable data transmission by selecting a forwarding relay and assigning access control policies according to their trust evaluations. Using the fuzzy logic approach, we choose the best relay node and set access control rules based on the results of their trust evaluation. In both phases, the trust parameters incorporate the experience, knowledge, and recommendations factors of each vehicle. TACR outperforms state-of-the-art procedures in simulations. The TACR technique boosts throughput by 11.25% and PDR by 8%. TACR reduces latency and overhead by 9.51% and 12.32%, respectively.
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页码:305 / 328
页数:23
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