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Anomaly detection using clustering for ad hoc networks -behavioral approach-
Author(s) -
Belacel Madani,
Belhadri Messabih
Publication year - 2012
Publication title -
computer engineering and applications journal
Language(s) - English
Resource type - Journals
eISSN - 2252-5459
pISSN - 2252-4274
DOI - 10.18495/comengapp.v1i1.6
Subject(s) - computer science , mobile ad hoc network , intrusion detection system , wireless ad hoc network , computer network , cluster analysis , optimized link state routing protocol , node (physics) , anomaly detection , vehicular ad hoc network , routing (electronic design automation) , routing protocol , distributed computing , wireless , computer security , data mining , network packet , artificial intelligence , engineering , telecommunications , structural engineering
Mobile ad hoc networks (MANETs) are multi-hop wireless networks of autonomous mobile nodes without any fixed infrastructure. In MANETs, it is difficult to detect malicious nodes because the network topology constantly changes due to node mobility. Intrusion detection is the means to identify the intrusive behaviors and provide useful information to intruded systems to respond fast and to avoid or reduce damages. The anomaly detection algorithms have the advantage because they can detect new types of attacks (zero-day attacks).In this paper, the Intrusion Detection System clustering-based (ID-Cluster) that fits the requirement of MANET is presented. This work addresses both routing layer misbehaviors issues, with main focuses on thwarting routing disruption attack Dynamic Source Routing (DSR). To validate the research, a case study is presented using the simulation with GloMoSim at different mobility levels. Simulation results show that proposed system can achieve desirable performance and meet the security requirement of MANET.

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