SVM-CASE: An SVM-based Context Aware Security Framework for Vehicular Ad-hoc Networks
Links to Fileshttps://ieeexplore.ieee.org/document/7391162
MetadataShow full item record
Type of Work5 pages
conference papers and proceedings pre-print
Citation of Original PublicationWenjia Li, Anupam Joshi, and Tim Finin, SVM-CASE: An SVM-based Context Aware Security Framework for Vehicular Ad-hoc Networks, 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall), DOI: 10.1109/VTCFall.2015.7391162
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© 2015 IEEE
vehicular ad hoc network
Support Vector Machine
UMBC Ebiquity Research Group
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.