RT-MOVICAB-IDS: Addressing real-time intrusion detection

  • Authors:
  • ÁLvaro Herrero;Martí Navarro;Emilio Corchado;Vicente JuliáN

  • Affiliations:
  • Department of Civil Engineering, University of Burgos, C/ Francisco de Vitoria s/n, 09006 Burgos, Spain;Departamento de Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain;Departamento de Informática y Automática, University of Salamanca, Plaza de la Merced s/n, 37008 Salamanca, Spain;Departamento de Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain

  • Venue:
  • Future Generation Computer Systems
  • Year:
  • 2013

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Abstract

This study presents a novel Hybrid Intelligent Intrusion Detection System (IDS) known as RT-MOVICAB-IDS that incorporates temporal control. One of its main goals is to facilitate real-time Intrusion Detection, as accurate and swift responses are crucial in this field, especially if automatic abortion mechanisms are running. The formulation of this hybrid IDS combines Artificial Neural Networks (ANN) and Case-Based Reasoning (CBR) within a Multi-Agent System (MAS) to detect intrusions in dynamic computer networks. Temporal restrictions are imposed on this IDS, in order to perform real/execution time processing and assure system response predictability. Therefore, a dynamic real-time multi-agent architecture for IDS is proposed in this study, allowing the addition of predictable agents (both reactive and deliberative). In particular, two of the deliberative agents deployed in this system incorporate temporal-bounded CBR. This upgraded CBR is based on an anytime approximation, which allows the adaptation of this Artificial Intelligence paradigm to real-time requirements. Experimental results using real data sets are presented which validate the performance of this novel hybrid IDS.