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An Artificial Immune System for Temporal Anomaly Detection Using Cell Activation Thresholds and Clonal Size Regulation with Homeostasis

2009-08Conference paper Restricted access
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datacite.subject.fosCiências Naturais::Ciências da Computação e da Informação
datacite.subject.fosEngenharia e Tecnologia::Engenharia Médica
dc.contributor.authorAntunes, Mário
dc.contributor.authorCorreia, Manuel E.
dc.date.accessioned2025-05-21T17:53:55Z
dc.date.available2025-05-21T17:53:55Z
dc.date.issued2009-08
dc.descriptionArticle number 5260652 - 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009, 3 August 2009 through 5 August 2009 - Code 78434
dc.description.abstractThis 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.eng
dc.description.sponsorshipThe authors acknowledge the facilities provided by the CRACS research unit, an INESC associate of the Faculty of Science, University of Porto.
dc.identifier.citationM. 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.
dc.identifier.doi10.1109/ijcbs.2009.59
dc.identifier.isbn978-0-7695-3739-9
dc.identifier.urihttp://hdl.handle.net/10400.8/12958
dc.language.isoeng
dc.peerreviewedyes
dc.publisherIEEE Canada
dc.relation.hasversionhttps://ieeexplore.ieee.org/document/5260652
dc.relation.ispartof2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing
dc.rights.uriN/A
dc.subjectArtificial Immune System
dc.subjectanomaly detection
dc.subjecthomeostasis
dc.subjectclonal size control
dc.subjecttunable activation threshold
dc.titleAn Artificial Immune System for Temporal Anomaly Detection Using Cell Activation Thresholds and Clonal Size Regulation with Homeostasiseng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2009-08
oaire.citation.conferencePlaceShanghai, China
oaire.citation.endPage326
oaire.citation.startPage323
oaire.citation.titleInternational Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameAntunes
person.givenNameMário
person.identifierR-000-NX4
person.identifier.ciencia-idAF10-7EDD-5153
person.identifier.orcid0000-0003-3448-6726
person.identifier.scopus-author-id25930820200
relation.isAuthorOfPublicatione3e87fb0-d1d6-44c3-985d-920a5560f8c1
relation.isAuthorOfPublication.latestForDiscoverye3e87fb0-d1d6-44c3-985d-920a5560f8c1

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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.
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