Skip to main content

Research Repository

Advanced Search

Information Fusion for Anomaly Detection with the Dendritic Cell Algorithm

Greensmith, Julie; Aickelin, Uwe; Tedesco, Gianni

Authors

Uwe Aickelin

Gianni Tedesco



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 http://eprints.nottingham.ac.uk/id/eprint/570
Publisher URL https://www.sciencedirect.com/science/article/abs/pii/S1566253509000384

Files





You might also like



Downloadable Citations