International Journal of Electrical, Electronics and Data Communication (IJEEDC)
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Statistics report
Mar. 2020
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 85
Paper Published : 1402
No. of Authors : 3795
  Journal Paper

Paper Title
A Mechanism to Classify The Black Hole Behavior of Vehicles in Vanets using One Class SVM

Abstract
Due to the nature such as the absence of fixed infrastructure, VANets are known to be very vulnerable to various internal and external attacks. Particularly, one of very common attack in vehicular ad hoc network is black hole attack. In this paper, an anomaly based mechanism is proposed to classify and detect the behavior of vehicles in Vanet. SUMO and ns2 to are used to simulate vehicular network and generate trace files. The system uses the features obtained from the trace file to detect the normal and abnormal behavior of vehicles using one class Support Vector Machine. Index Terms- Anomaly detection, Black hole attack, one-class SVM, Security, Vanet.


Author - Nan Zarchi Kyaw, Thetzaw Aye

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| Published on 2018-12-11
   
   
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