SVM-CASE: An SVM-based Context Aware Security Framework for Vehicular Ad-hoc Networks
dc.contributor.author | Li, Wenjia | |
dc.contributor.author | Joshi, Anupam | |
dc.contributor.author | Finin, Tim | |
dc.date.accessioned | 2018-11-01T15:01:45Z | |
dc.date.available | 2018-11-01T15:01:45Z | |
dc.date.issued | 2016-01-28 | |
dc.description | 82nd IEEE Vehicular Technology Conference | en_US |
dc.description.abstract | 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. | en_US |
dc.description.uri | https://ieeexplore.ieee.org/document/7391162 | en_US |
dc.format.extent | 5 pages | en_US |
dc.genre | conference papers and proceedings pre-print | en_US |
dc.identifier | doi:10.13016/M2FQ9Q89Z | |
dc.identifier.citation | Wenjia 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 | en_US |
dc.identifier.uri | 10.1109/VTCFall.2015.7391162 | |
dc.identifier.uri | http://hdl.handle.net/11603/11817 | |
dc.language.iso | en_US | en_US |
dc.publisher | IEEE | en_US |
dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
dc.relation.ispartof | UMBC Faculty Collection | |
dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
dc.rights | © 2015 IEEE | |
dc.subject | security | en_US |
dc.subject | malicious attack | en_US |
dc.subject | context awareness | en_US |
dc.subject | vehicular ad hoc network | en_US |
dc.subject | Support Vector Machine | en_US |
dc.subject | UMBC Ebiquity Research Group | en_US |
dc.title | SVM-CASE: An SVM-based Context Aware Security Framework for Vehicular Ad-hoc Networks | en_US |
dc.type | Text | en_US |