Information Fusion for Anomaly Detection with the Dendritic Cell Algorithm

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Greensmith, Julie, Aickelin, Uwe and Tedesco, Gianni (2007) Information Fusion for Anomaly Detection with the Dendritic Cell Algorithm. Information Fusion . (In Press)

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Abstract

Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system, providing the initial detection of pathogenic invaders. Research into this family of cells has revealed that they

perform information fusion which directs immune responses. We have derived a Dendritic Cell Algorithm based on

the functionality of these cells, by modelling the biological signals and differentiation pathways to build a control mechanism for an artificial immune system. We present algorithmic details in addition to experimental results, when the algorithm was applied to anomaly detection for the detection of port scans. The results show the Dendritic Cell Algorithm is successful at detecting port scans.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/1017425
Keywords: Information Fusion, Anomaly Detection, Dendritic Cell, Algorithm, modelling, biological signals, differentiation pathways
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User: Aickelin, Professor Uwe
Date Deposited: 30 Oct 2007 16:28
Last Modified: 04 May 2020 20:28
URI: https://eprints.nottingham.ac.uk/id/eprint/570

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