Cluster Head Based Intrusion Detection System for Black Hole Attacks in Wireless Ad Hoc Networks using 2 Level Fuzzy Logic System

Joseph, Christeena and Kishoreraja, P.C. and Baskar, Radhika (2021) Cluster Head Based Intrusion Detection System for Black Hole Attacks in Wireless Ad Hoc Networks using 2 Level Fuzzy Logic System. In: I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India.

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Abstract

Ad hoc networks are autonomous and infrastructure-less wireless systems where nodes act as routers and hosts. Security is the primary issue for the functionality of these networks. Security for ad hoc networks can be incorporated by prevention and detection mechanisms. This research work focuses on a two-level fuzzy-based intrusion detection system for identifying black hole attacks in ad hoc networks. This method can reduce the complexity of the rule base of the fuzzy inference system. To reduce the complexity of detection, communication overhead and to make the detection scheme energy efficient, further, a cluster-head-based intrusion detection system is designed and implemented. The impact on network performance with no attack, with black hole attack, and with intrusion detection scheme deployed in all nodes and cluster heads are analyzed. The proposed cluster-based 2 level fuzzy logic intrusion detection mechanism was able to achieve the detection rate and accuracy to a maximum of 100%,false alarm rate to 0% and detection delay to in varying attacker scenario.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: adhoc networks blackhole attacks cluster head ids fuzzy logic
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor IV
Date Deposited: 11 Jun 2021 08:02
Last Modified: 11 Jun 2021 08:02
URI: https://eprints.eudl.eu/id/eprint/3871

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