Information Fusion for Anomaly Detection with the Dendritic Cell Algorithm

Greensmith, Julie; Aickelin, Uwe; Tedesco, Gianni

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.

Citation

Greensmith, J., Aickelin, U., & Tedesco, G. (2010). Information Fusion for Anomaly Detection with the Dendritic Cell Algorithm. Information Fusion, 11(1), 21-34. https://doi.org/10.1016/j.inffus.2009.04.006

• Journal Article Type: Article
• Acceptance Date: Apr 1, 2009
• Online Publication Date: Apr 23, 2009
• Publication Date: 2010-01
• Deposit Date: Oct 30, 2007
• Publicly Available Date: Apr 23, 2009
• Journal: Information Fusion
• Print ISSN: 1566-2535
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 11
• Issue: 1
• Pages: 21-34
• DOI: https://doi.org/10.1016/j.inffus.2009.04.006
• Keywords: Information Fusion, Anomaly Detection, Dendritic Cell, Algorithm, modelling, biological signals, differentiation pathways
• Public URL: https://nottingham-repository.worktribe.com/output/1017425
• Publisher URL: https://www.sciencedirect.com/science/article/abs/pii/S1566253509000384