Information fusion in the immune system

Twycross, Jamie and Aickelin, Uwe (2010) Information fusion in the immune system. Information Fusion, 11 (1). pp. 35-44. ISSN 1566-2535

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Biologically-inspired methods such as evolutionary algorithms and neural networks are proving useful in

the field of information fusion. Artificial immune systems (AISs) are a biologically-inspired approach which take inspiration from the biological immune system. Interestingly, recent research has shown how AISs which use multi-level information sources as input data can be used to build effective algorithms for realtime computer intrusion detection. This research is based on biological information fusion mechanisms used by the human immune system and as such might be of interest to the information

fusion community. The aim of this paper is to present a summary of some of the biological information fusion mechanisms seen in the human immune system, and of how these mechanisms have been implemented as AISs.

Item Type: Article
Additional Information: NOTICE: this is the author’s version of a work that was accepted for publication in Information Fusion. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Information Fusion, 11,1 (2010), doi: 10.1016/j.inffus.2009.04.008
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number:
Depositing User: Aickelin, Professor Uwe
Date Deposited: 18 Jul 2013 12:39
Last Modified: 04 May 2020 20:25

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