A trust based model (TBM) to detect rogue nodes in vehicular ad-hoc networks (VANETS)
Kuldeep Narayan Tripathi () and
S. C. Sharma
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Kuldeep Narayan Tripathi: Indian Institute of Technology Roorkee
S. C. Sharma: Indian Institute of Technology Roorkee
International Journal of System Assurance Engineering and Management, 2020, vol. 11, issue 2, No 16, 426-440
Abstract:
Abstract Due to the exponential growth in the automobile industry, we need intelligence transportation system. Vehicular ad-hoc network (VANET), a part of the intelligence transportation system is the network created by vehicles. Security is the main issue in vehicular ad-hoc network. Many intruders try to use the vulnerability presents in the vehicular network. In VANET communication between two nodes, may involves multiple intermediate nodes to forward the data due to low transmission range. The intermediate nodes must be trustworthy enough to be a part of the communication process. Rogue or malicious nodes can accept the data and drop the data in between source to destination. In this paper, we proposed a trust based model to detect rogue nodes in a vehicular network. The proposed model first estimates the trust value of the nodes and based on that identifies the rogue nodes in the network. We select only trustworthy nodes to relay the data in the routing process. The simulation and performance evaluation of the proposed model performed with the help of network simulator (NS-2). We evaluate the performance of the network based on the four performance matrices i.e. successful packet delivery fraction, throughput, routing load and end to end delay. The simulation result shows that the proposed model enhances network performance significantly.
Keywords: Trust; Rogue nodes; Vehicular ad-hoc network; Entity centric trust; Direct trust; Indirect trust; Black hole attack; NS-2 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ijsaem:v:11:y:2020:i:2:d:10.1007_s13198-019-00871-0
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DOI: 10.1007/s13198-019-00871-0
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