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Temporal Anomaly Detection: An Artificial Immune Approach Based on T Cell Activation, Clonal Size Regulation and Homeostasis

Conference paper
First Online:
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 680)

Abstract

This paper presents an artificial immune system (AIS) based on Grossman’s tunable activation threshold (TAT) for temporal anomaly detection. We describe the generic AIS framework and the TAT model adopted for simulating T Cells behaviour, emphasizing two novel important features: the temporal dynamic adjustment of T Cells clonal size and its associated homeostasis mechanism. We also present some promising results obtained with artificially generated data sets, aiming to test the appropriateness of using TAT in dynamic changing environments, to distinguish new unseen patterns as part of what should be detected as normal or as anomalous. We conclude by discussing results obtained thus far with artificially generated data sets.

Keywords

Artificial immune systems Pattern recognition Anomaly detection Homeostasis 
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Notes

Acknowledgements

The authors acknowledge the facilities provided by the CRACS research unit, an INESC associate of the Faculty of Science, University of Porto.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.School of Technology and ManagementPolytechnic Institute of LeiriaLeiriaPortugal

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