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Immunity-Inspired Intrusion Detection System Framework


M?rio J. Antunes, Rui Vasco Monteiro, S?rgio T. Magalh?es, Manuel E. Correia, Henrique D. Santos


Vol. 6  No. 5  pp. 235-244


In this paper we propose a novel framework for Intrusion Detection Systems (IDS). Its main goals are: 1) the characterization of normal traffic through the definition of a normality profile based on the relationship among hosts in the network and 2) The application of theoretical immunological concepts to provide adaptability based on memory and learning from previous attacks. We proceed by presenting important principles and concepts relevant to the description and categorization of IDS, and then describe the main benefits that can be obtained from an Artificial Immune System (AIS) approach for IDS. We conclude by proposing a novel extension to the Common Intrusion Detection Framework (CIDF) capable of accommodating our initial goals. We believe that both approaches included together in an IDS will facilitate and improve its operation in a distributed and heterogeneous environment.


Intrusion detection, immunology, immunity-based algorithms, security, anomaly detection