Title: MAM-ISSIDS: multi-agent model-based intelligent and self-sharing intrusion detection system for distributed network

Authors: K. Anusha; E. Sathiyamoorthy

Addresses: School of Information Technology and Engineering, VIT University, Vellore, Tamil Nadu, 632014, India ' School of Information Technology and Engineering, VIT University, Vellore, Tamil Nadu, 632014, India

Abstract: Intrusion detection system (IDS) is essential for protecting the computer networks from various threats and attacks. The autonomous multi-agent model (MAM) architecture is a scalable and smart alternative to leverage the strengths of the host and network based IDS. This paper proposes MAM-based intelligent and self-sharing IDS (MAM-ISSIDS) for distributed network to detect the host, network and web service attacks. Feature selection is performed by using the integrated particle swarm optimisation-genetic algorithm (PSO-GA) approach. The intuitionistic fuzzy rules are used to formulate the rules of the existing attackers for the benchmark dataset. The ontology structure is used to share the rules in network. The MAM is used for detecting the occurrence of abnormal traffic resulting due to the intrusion attacks. The proposed system achieves higher attack detection rate, accuracy and lower false positive rate due to the distributed sharing strategy of the MAM.

Keywords: intrusion detection; intuitionistic fuzzy rules; multi-agent model; MAM; particle swarm optimisation-genetic algorithm; PSO-GA.

DOI: 10.1504/IJICS.2017.087567

International Journal of Information and Computer Security, 2017 Vol.9 No.4, pp.361 - 386

Received: 26 Mar 2016
Accepted: 24 Aug 2016

Published online: 19 Oct 2017 *

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