82nd IEEE Vehicular Technology Conference

SVM-CASE: An SVM-based Context Aware Security Framework for Vehicular Ad-hoc Networks

Wenjia Li, Anupam Joshi, and Tim Finin

September 6, 2015

Vehicular Ad-hoc Networks (VANETs) are known to be very susceptible to various malicious attacks. To detect and mitigate these malicious attacks, many security mechanisms have been studied for VANETs. In this paper, we propose a context aware security framework for VANETs that uses the Support Vector Machine (SVM) algorithm to automatically determine the boundary between malicious nodes and normal ones. Compared to the existing security solutions for VANETs, The proposed framework is more resilient to context changes that are common in VANETs, such as those due to malicious nodes altering their attack patterns over time or rapid changes in environmental factors, such as the motion speed and transmission range. We compare our framework to existing approaches and present evaluation results obtained from simulation studies.

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Tags: cyber security, learning, vanet, vehicles

Type: InProceedings

Publisher: IEEE

Downloads: 1164 downloads