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Intrusion detection system classifier for VANET based on pre-processing feature extraction
conference contribution
posted on 2019-01-01, 00:00 authored by Ayoob Ayoob, Ghaith Dh Khalil, Morshed ChowdhuryMorshed Chowdhury, Robin Ram Mohan DossRobin Ram Mohan DossVehicular Ad-hoc Networks (VANETs) are gaining much interest and research efforts over recent years for it offers enhanced safety and improved travel comfort. However, security threats that are either seen in the ad-hoc networks or unique to VANET present considerable challenges. In this paper, we are presenting the intrusion detection classifier for VANET base on pre-processing feature extraction. This ID infrastructure novel is mainly introducing a new design feature for extraction mechanism a pre-processing feature-based classifier. In the beginning, we will extract the traffic stream structures and vehicle location features in the VANET model. Later an Algorithm Pre-processing feature-based classifier was designed for evaluating the IDS by using hierarchy learning process. Finally, an additional two-step validation mechanism was used to determine the abnormal vehicle messages accurately. The proposed method has better finding accuracy, stability, processing efficiency, and communication load.
History
Event
Future Network Systems and Security. Conference (2019 : Melbourne, Victoria)Volume
1113Series
Communications in Computer and Information SciencePagination
3 - 22Publisher
SpringerLocation
Melbourne, VictoriaPlace of publication
Cham, SwitzerlandStart date
2019-11-27End date
2019-11-29eISSN
1865-0937ISBN-13
9783030343521Language
engPublication classification
E1 Full written paper - refereedEditor/Contributor(s)
R Ram Mohan Doss, S Piramuthu, W ZhouTitle of proceedings
FNSS 2019 : Future Network Systems and Security 5th International Conference, FNSS 2019 Melbourne, VIC, Australia, November 27–29, 2019 ProceedingsUsage metrics
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