Visible to the public Monitoring Algorithm in Malicious Vehicular Adhoc Networks

TitleMonitoring Algorithm in Malicious Vehicular Adhoc Networks
Publication TypeConference Paper
Year of Publication2020
AuthorsPadmapriya, S., Valli, R., Jayekumar, M.
Conference Name2020 International Conference on System, Computation, Automation and Networking (ICSCAN)
Date PublishedJuly 2020
ISBN Number978-1-7281-6202-7
Keywordsad hoc network, authentication, Clustering algorithms, compositionality, distrust value, malicious vehicle detection, Metrics, Monitoring, privacy, pubcrawl, resilience, Resiliency, Safety, security, threshold value, VANET, vehicular ad hoc networks

Vehicular Adhoc Networks (VANETs) ensures road safety by communicating with a set of smart vehicles. VANET is a subset of Mobile Adhoc Networks (MANETs). VANET enabled vehicles helps in establishing communication services among one another or with the Road Side Unit (RSU). Information transmitted in VANET is distributed in an open access environment and hence security is one of the most critical issues related to VANET. Although each vehicle is not a source of all communications, most contact depends on the information that other vehicles receive from it. That vehicle must be able to assess, determine and respond locally on the information obtained from other vehicles to protect VANET from malicious act. Of this reason, message verification in VANET is more difficult due to the protection and privacy issues of the participating vehicles. To overcome security threats, we propose Monitoring Algorithm that detects malicious nodes based on the pre-selected threshold value. The threshold value is compared with the distrust value which is inherently tagged with each vehicle. The proposed Monitoring Algorithm not only detects malicious vehicles, but also isolates the malicious vehicles from the network. The proposed technique is simulated using Network Simulator2 (NS2) tool. The simulation result illustrated that the proposed Monitoring Algorithm outperforms the existing algorithms in terms of malicious node detection, network delay, packet delivery ratio and throughput, thereby uplifting the overall performance of the network.

Citation Keypadmapriya_monitoring_2020