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The Use of Statistical Signatures to Detect Anomalies in Computer Network

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Analysis and Simulation of Electrical and Computer Systems

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 324))

Abstract

This article presents a new approach for detecting anomalies in the computer network. The approach is based on the determination of the network traffic statistical parameters in case of normal condition. When network anomaly happens, usually more than one statistical parameter is change. A set of parameters that have changed can be used to identify threats. Currently, anomaly detection mechanisms used in the network traffic are computationally complex and cannot be used in case of high speed connection. The presented method does not guarantee the anomaly identification but can be used as one of the indicators used for the isolation of suspicious flows (through ongoing modifications the routing or switching rules). Separated flow is subjected to further analysis with use of classical methods for anomaly detection. With this approach it is possible to make a rough anomaly identification in the core of high speed computer network.

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Author information

Authors and Affiliations

  1. Department of Distributed Systems, Rzeszow University of Technology, al. Powstańców Warszawy 12, 35-959, Rzeszów, Poland

    Marek Bolanowski & Andrzej Paszkiewicz

Authors
  1. Marek Bolanowski
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  2. Andrzej Paszkiewicz
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Corresponding author

Correspondence to Marek Bolanowski .

Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering Fundamentals, Rzeszów University of Technology, Rzeszów, Poland

    Lesław Gołębiowski

  2. Department of Electrical and Computer Engineering Fundamentals, Rzeszów University of Technology, Rzeszów, Poland

    Damian Mazur

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Bolanowski, M., Paszkiewicz, A. (2015). The Use of Statistical Signatures to Detect Anomalies in Computer Network. In: Gołębiowski, L., Mazur, D. (eds) Analysis and Simulation of Electrical and Computer Systems. Lecture Notes in Electrical Engineering, vol 324. Springer, Cham. https://doi.org/10.1007/978-3-319-11248-0_19

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  • DOI: https://doi.org/10.1007/978-3-319-11248-0_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11247-3

  • Online ISBN: 978-3-319-11248-0

  • eBook Packages: EngineeringEngineering (R0)

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