Information fusion for anomaly detection with the dendritic cell algorithm

Authors:
Julie Greensmith;Uwe Aickelin;Gianni Tedesco
Affiliations:
School of Computer Science, University of Nottingham, Nottingham NG8 1BB, UK;School of Computer Science, University of Nottingham, Nottingham NG8 1BB, UK;School of Computer Science, University of Nottingham, Nottingham NG8 1BB, UK
Venue:
Information Fusion
Year:
2010

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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.