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

dc.contributor.authorLi, Wenjia
dc.contributor.authorJoshi, Anupam
dc.contributor.authorFinin, Tim
dc.date.accessioned2018-11-01T15:01:45Z
dc.date.available2018-11-01T15:01:45Z
dc.date.issued2016-01-28
dc.description82nd IEEE Vehicular Technology Conferenceen_US
dc.description.abstractVehicular 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.urihttps://ieeexplore.ieee.org/document/7391162en_US
dc.format.extent5 pagesen_US
dc.genreconference papers and proceedings pre-printen_US
dc.identifierdoi:10.13016/M2FQ9Q89Z
dc.identifier.citationWenjia 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.2015.7391162en_US
dc.identifier.uri10.1109/VTCFall.2015.7391162
dc.identifier.urihttp://hdl.handle.net/11603/11817
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis 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.subjectsecurityen_US
dc.subjectmalicious attacken_US
dc.subjectcontext awarenessen_US
dc.subjectvehicular ad hoc networken_US
dc.subjectSupport Vector Machineen_US
dc.subjectUMBC Ebiquity Research Groupen_US
dc.titleSVM-CASE: An SVM-based Context Aware Security Framework for Vehicular Ad-hoc Networksen_US
dc.typeTexten_US

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