Publication
Towards an immune-inspired temporal anomaly detection algorithm based on tunable activation thresholds
| dc.contributor.author | Antunes, Mário | |
| dc.contributor.author | Correia, Manuel | |
| dc.contributor.author | Carneiro, Jorge | |
| dc.date.accessioned | 2025-06-06T16:24:05Z | |
| dc.date.available | 2025-06-06T16:24:05Z | |
| dc.date.issued | 2009-01 | |
| dc.description | BIOSIGNALS 2009 - Proceedings of the 2nd International Conference on Bio-Inspired Systems and Signal Processing Pages 357 - 362 2009 2nd International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2009 - 14 January 2009 through 17 January 2009 - Code 76662 | |
| dc.description.abstract | The detection of anomalies in computer environments, like network intrusion detection, computer virus or spam classification, is usually based on some form of pattern search on a database of "signatures" for known anomalies. Although very successful and widely deployed, these approaches are only able to cope with anomalous events that have already been seen. To cope with these weaknesses, the "behaviour" based systems has been deployed. Although conceptually more appealing, they have still an impractical high rate of false alarms. The vertebrate Immune System is an emergent and appealing metaphor for new ideas on anomaly detection, being already adopted some algorithms and theoretical theories in particular fields, such as network intrusion detection. In this paper we present a temporal anomaly detection architecture based on the Grossman's Tunable Activation Threshold (TAT) hypothesis. The basic idea is that the repertoire of immune cells is constantly tuned according to the cells temporal interactions with the environment and yet retains responsiveness to an open-ended set of abnormal events. We describe some preliminary work on the development of an anomaly detection algorithm derived from TAT and present the results obtained thus far using some synthetic data-sets. | eng |
| dc.description.sponsorship | The authors acknowledge the facilities and research environment gracefully provided by the CRACS (Center for Research in Advanced Computing Systems) research unit, an INESC associate of the Faculty of Science, University of Porto. | |
| dc.identifier.citation | Antunes, M., Correia, M., & Carneiro, J. (2009, January). Towards an immune-inspired temporal anomaly detection algorithm based on tunable activation thresholds. In International Conference on Bio-inspired Systems and Signal Processing (Vol. 1, pp. 357-362). SCITEPRESS. | |
| dc.identifier.doi | 10.5220/0001553303570362 | |
| dc.identifier.isbn | 978-989-8111-65-4 | |
| dc.identifier.uri | http://hdl.handle.net/10400.8/13184 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | SciTePress - Science and and Technology Publications | |
| dc.relation.hasversion | https://www.scitepress.org/PublishedPapers/2009/15533/ | |
| dc.relation.ispartof | Proceedings of the International Conference on Bio-inspired Systems and Signal Processing | |
| dc.rights.uri | N/A | |
| dc.subject | Artificial immune system | |
| dc.subject | Anomaly detection | |
| dc.subject | Tunable activation threshold | |
| dc.subject | T-cell simulation and modelling | |
| dc.subject | Pattern recognition | |
| dc.title | Towards an immune-inspired temporal anomaly detection algorithm based on tunable activation thresholds | eng |
| dc.type | conference paper | |
| dspace.entity.type | Publication | |
| oaire.citation.conferenceDate | 2009-01 | |
| oaire.citation.conferencePlace | Porto, Portugal | |
| oaire.citation.endPage | 362 | |
| oaire.citation.startPage | 357 | |
| oaire.citation.title | Proceedings of the International Conference on Bio-inspired Systems and Signal Processing | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| person.familyName | Antunes | |
| person.givenName | Mário | |
| person.identifier | R-000-NX4 | |
| person.identifier.ciencia-id | AF10-7EDD-5153 | |
| person.identifier.orcid | 0000-0003-3448-6726 | |
| person.identifier.scopus-author-id | 25930820200 | |
| relation.isAuthorOfPublication | e3e87fb0-d1d6-44c3-985d-920a5560f8c1 | |
| relation.isAuthorOfPublication.latestForDiscovery | e3e87fb0-d1d6-44c3-985d-920a5560f8c1 |
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- The detection of anomalies in computer environments, like network intrusion detection, computer virus or spam classification, is usually based on some form of pattern search on a database of "signatures" for known anomalies. Although very successful and widely deployed, these approaches are only able to cope with anomalous events that have already been seen. To cope with these weaknesses, the "behaviour" based systems has been deployed. Although conceptually more appealing, they have still an impractical high rate of false alarms. The vertebrate Immune System is an emergent and appealing metaphor for new ideas on anomaly detection, being already adopted some algorithms and theoretical theories in particular fields, such as network intrusion detection. In this paper we present a temporal anomaly detection architecture based on the Grossman's Tunable Activation Threshold (TAT) hypothesis. The basic idea is that the repertoire of immune cells is constantly tuned according to the cells temporal interactions with the environment and yet retains responsiveness to an open-ended set of abnormal events. We describe some preliminary work on the development of an anomaly detection algorithm derived from TAT and present the results obtained thus far using some synthetic data-sets.
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