• DocumentCode
    1613968
  • Title

    An artificial immune system approach to anomaly detection in multimedia ambient intelligence

  • Author

    Gianini, Gabriele ; Anisetti, Marco ; Azzini, Antonia ; Bellandi, Valerio ; Damiani, Ernesto ; Marrara, Stefania

  • Author_Institution
    Dipt. di Tecnol. dell´´Inf., Univ. degli Studi di Milano, Crema, Italy
  • fYear
    2009
  • Firstpage
    502
  • Lastpage
    506
  • Abstract
    Artificial Immune Systems are inspired by biological immune systems, and are characterized by interesting properties such as error tolerance, adaptation and self-monitoring. An area where they found wide application is anomaly detection in information systems, including intrusion detection. In this work we propose to extend the Artificial Immune System (AIS) paradigm from its typical application domain, computer system security, to ambient intelligence. AISs can be used to respond adaptively to real word anomalies in controlled environments. Here the counterpart of perceptual functions and detection capabilities can be provided by device intelligence, e.g. in terms of multimedia interpretation.
  • Keywords
    artificial immune systems; artificial intelligence; information systems; multimedia computing; security of data; adaptation; anomaly detection; artificial immune system; biological immune systems; computer system security; error tolerance; information systems; intrusion detection; multimedia ambient intelligence; self-monitoring; Ambient intelligence; Application software; Artificial immune systems; Biology computing; Computer applications; Computer errors; Immune system; Information systems; Intrusion detection; Multimedia systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Ecosystems and Technologies, 2009. DEST '09. 3rd IEEE International Conference on
  • Conference_Location
    Istanbul
  • Print_ISBN
    978-1-4244-2345-3
  • Electronic_ISBN
    978-1-4244-2346-0
  • Type

    conf

  • DOI
    10.1109/DEST.2009.5276702
  • Filename
    5276702