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Information Fusion for Anomaly Detection with the Dendritic Cell Algorithm

Greensmith, Julie; Aickelin, Uwe; Tedesco, Gianni

Authors

Julie Greensmith

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.

Journal Article Type Article
Publication Date 2010-01
Journal Information Fusion
Print ISSN 1566-2535
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 11
Issue 1
Pages 21-34
APA6 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
DOI https://doi.org/10.1016/j.inffus.2009.04.006
Keywords Information Fusion, Anomaly Detection, Dendritic Cell, Algorithm, modelling, biological signals, differentiation pathways
Publisher URL https://www.sciencedirect.com/science/article/abs/pii/S1566253509000384
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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