An Ecological Approach to Anomaly Detection: The EIA Model

  • Pedro Pinacho
  • Iván Pau
  • Max Chacón
  • Sergio Sánchez
Conference paper

DOI: 10.1007/978-3-642-33757-4_18

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7597)
Cite this paper as:
Pinacho P., Pau I., Chacón M., Sánchez S. (2012) An Ecological Approach to Anomaly Detection: The EIA Model. In: Coello Coello C.A., Greensmith J., Krasnogor N., Liò P., Nicosia G., Pavone M. (eds) Artificial Immune Systems. ICARIS 2012. Lecture Notes in Computer Science, vol 7597. Springer, Berlin, Heidelberg

Abstract

The presented work proposes a new approach for anomaly detection. This approach is based on changes in a population of evolving agents under stress. If conditions are appropriate, changes in the population (modeled by the bioindicators) are representative of the alterations to the environment. This approach, based on an ecological view, improves functionally traditional approaches to the detection of anomalies. To verify this assertion, experiments based on Network Intrussion Detection Systems are presented. The results are compared with the behaviour of other bioinspired approaches and machine learning techniques.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Pedro Pinacho
    • 1
  • Iván Pau
    • 3
  • Max Chacón
    • 2
  • Sergio Sánchez
    • 3
  1. 1.Escuela InformäticaUniversidad Santo TomásConcepciónChile
  2. 2.Departamento de Ingeniería InformáticaUniversidad de SantiagoSantiagoChile
  3. 3.EUIT TelecomunicaciónTechnical University of MadridSpain

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