Abstract
The vast majority of existing Intrusion Detection Systems (IDS) incorporates static knowledge bases, which contain information corresponding to specific attack patterns. Although such knowledge bases can gradually expand, to be able to detect new attacks, this requires the maintenance of an expert. This paper describes a potential application of computationally evolving intelligent behaviour in conjunction with network intrusion detection. Our aim is to develop a standalone Network Intrusion Detection System (NIDS), capable of working in offline and online mode by evolving its structure and parameters in order to prevent both known and novel intrusions.
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Lekkas, S., Mikhailov, D.L. (2008). Towards the Development of OMNIVORE: An Evolving Intelligent Intrusion Detection System. In: Ellis, R., Allen, T., Petridis, M. (eds) Applications and Innovations in Intelligent Systems XV. SGAI 2007. Springer, London. https://doi.org/10.1007/978-1-84800-086-5_22
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DOI: https://doi.org/10.1007/978-1-84800-086-5_22
Publisher Name: Springer, London
Print ISBN: 978-1-84800-085-8
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