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This paper presents an Artificial Immune System (AIS) based on Grossman's Tunable Activation Threshold (TAT) for anomaly detection. We describe the immunological metaphor and the algorithm adopted for T-cells, emphasizing two important features: the temporal dynamic adjustment of T-cells clonal size and its associated homeostasis mechanism. We 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. | 865.22 KB | Adobe PDF |
Authors
Advisor(s)
Abstract(s)
This paper presents an Artificial Immune System (AIS) based on Grossman's Tunable Activation Threshold (TAT) for anomaly detection. We describe the immunological metaphor and the algorithm adopted for T-cells, emphasizing two important features: the temporal dynamic adjustment of T-cells clonal size and its associated homeostasis mechanism. We 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.
Description
Article number 5260652 - 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009, 3 August 2009 through 5 August 2009 - Code 78434
Keywords
Artificial Immune System anomaly detection homeostasis clonal size control tunable activation threshold
Citation
M. J. Antunes and M. E. Correia, "An Artificial Immune System for Temporal Anomaly Detection Using Cell Activation Thresholds and Clonal Size Regulation with Homeostasis," 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, Shanghai, China, 2009, pp. 323-326, doi: https://doi.org/10.1109/IJCBS.2009.59.
Publisher
IEEE Canada
CC License
Without CC licence