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Intrusion detection system classifier for VANET based on pre-processing feature extraction

Version 2 2024-06-03, 11:52
Version 1 2019-11-02, 16:42
conference contribution
posted on 2024-06-03, 11:52 authored by Ayoob Ayoob, Ghaith Khalil, Morshed ChowdhuryMorshed Chowdhury, Robin Ram Mohan DossRobin Ram Mohan Doss
Vehicular 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

Volume

1113

Pagination

3-22

Location

Melbourne, Victoria

Start date

2019-11-27

End date

2019-11-29

eISSN

1865-0937

ISBN-13

9783030343521

Language

eng

Publication classification

E1 Full written paper - refereed

Editor/Contributor(s)

Ram Mohan Doss R, Piramuthu S, Zhou W

Title of proceedings

FNSS 2019 : Future Network Systems and Security 5th International Conference, FNSS 2019 Melbourne, VIC, Australia, November 27–29, 2019 Proceedings

Event

Future Network Systems and Security. Conference (2019 : Melbourne, Victoria)

Publisher

Springer

Place of publication

Cham, Switzerland

Series

Communications in Computer and Information Science

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