Dynamic event classification for intrusion and false alarm detection in vehicular ad hoc networks
by Mohammed G.H. Al Zamil; Samer Samarah
International Journal of Information and Communication Technology (IJICT), Vol. 8, No. 2/3, 2016

Abstract: Several classification techniques have been proposed as a basis to build intrusion detection systems for vehicular ad-hoc networks. In this paper, we proposed a dynamic event classification technique to categorise communication messages for the purpose of detecting intrusions and false alarms. The contributions of this research are to: 1) propose an efficient binary classification technique to evaluate the plausibility of communication messages in VANETs based on a set of semantic patterns of actions; 2) apply a mechanism to construct association rules that handle the representation of ad-hoc conditions. The proposed technique relies on defining the classification task as an optimisation problem that maximises true-positives and minimises false-positives. A set of experiments have been performed in order to evaluate the proposed technique using two different datasets. The results indicated that our proposed technique outperformed state-of-the-art classification techniques and efficiently detect intrusions and false alarms.

Online publication date: Sun, 21-Feb-2016

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