T Cell Receptor Signalling Inspired Kernel Density Estimation and Anomaly Detection

Authors:
Nick D. Owens;Andy Greensted;Jon Timmis;Andy Tyrrell
Affiliations:
Department of Electronics, University of York, York, UK;Department of Electronics, University of York, York, UK;Department of Electronics, University of York, York, UK and Department of Computer Science, University of York, York, UK;Department of Electronics, University of York, York, UK
Venue:
ICARIS '09 Proceedings of the 8th International Conference on Artificial Immune Systems
Year:
2009

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Abstract

The T cell is able to perform fine-grained anomaly detection via its T Cell Receptor and intracellular signalling networks. We abstract from models of T Cell signalling to develop a new Artificial Immune System concepts involving the internal components of the TCR. We show that the concepts of receptor signalling have a natural interpretation as Parzen Window Kernel Density Estimation applied to anomaly detection. We then demonstrate how the dynamic nature of the receptors allows anomaly detection when probability distributions vary in time.