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Data Traffic Monitoring and Analysis pp 148–183Cite as

A Methodological Overview on Anomaly Detection

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Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 7754))

Abstract

In this Chapter we give an overview of statistical methods for anomaly detection (AD), thereby targeting an audience of practitioners with general knowledge of statistics. We focus on the applicability of the methods by stating and comparing the conditions in which they can be applied and by discussing the parameters that need to be set.

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Authors and Affiliations

  1. University of Pisa, Pisa, Italy

    Christian Callegari, Stefano Giordano, Michele Pagano & Teresa Pepe

  2. University of Salento, Lecce, Italy

    Angelo Coluccia & Fabio Ricciato

  3. Forschungszentrum Telekommunikation Wien, Vienna, Austria

    Alessandro D’Alconzo & Fabio Ricciato

  4. TNO, Delft, The Netherlands

    Wendy Ellens & Piotr Z̊uraniewski

  5. Korteweg-de Vries Institute for Mathematics, University of Amsterdam, The Netherlands

    Michel Mandjes & Piotr Z̊uraniewski

  6. Eurandom, Eindhoven University of Technology, Eindhoven, The Netherlands

    Michel Mandjes

  7. CWI, Amsterdam, The Netherlands

    Michel Mandjes

  8. AGH University of Science and Technology, Krakow, Poland

    Piotr Z̊uraniewski

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  1. Networking and Security Department, Eurécom, 450 Route des Chappes, 06410, Biot, France

    Ernst Biersack

  2. Department of Information Engineering, University of Pisa, Via Caruso 16, 56122, Pisa, Italy

    Christian Callegari

  3. Facults of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000, Zagreb, Croatia

    Maja Matijasevic

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Callegari, C. et al. (2013). A Methodological Overview on Anomaly Detection. In: Biersack, E., Callegari, C., Matijasevic, M. (eds) Data Traffic Monitoring and Analysis. Lecture Notes in Computer Science, vol 7754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36784-7_7

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