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International Internet of Things Summit

IoT360 2015: Internet of Things. IoT Infrastructures pp 210–221Cite as

A Data Plane Approach for Detecting Control Plane Anomalies in Mobile Networks

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Abstract

This paper proposes an anomaly detection framework that utilizes key performance indicators (KPIs) and traffic measurements to identify in real-time misbehaving mobile devices that contribute to signaling overloads in cellular networks. The detection algorithm selects the devices to monitor and adjusts its own parameters based on KPIs, then computes various features from Internet traffic that capture both sudden and long term changes in behavior, and finally combines the information gathered from the individual features using a random neural network in order to detect anomalous users. The approach is validated using data generated by a detailed mobile network simulator.

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Acknowledgments

This work was supported in part by the EU FP7 project NEMESYS under grant agreement no. 317888.

Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Imperial College, London, SW7 2BT, UK

    Omer H. Abdelrahman & Erol Gelenbe

Authors
  1. Omer H. Abdelrahman
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  2. Erol Gelenbe
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Corresponding author

Correspondence to Omer H. Abdelrahman .

Editor information

Editors and Affiliations

  1. IBM Research, Haifa, Israel

    Benny Mandler

  2. CONNECT Centre, Trinity College, University of Dublin, Dublin, Ireland

    Johann Marquez-Barja

  3. GTA/PEE-COPPE/DEL-Poli, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil

    Miguel Elias Mitre Campista

  4. Faculty of Materials Science and Technology in Trnava, Slovak University of Technology in Bratislava, Trnava, Slovakia

    Dagmar Cagáňová

  5. Institut Télécom SudParis, Evry, France

    Hakima Chaouchi

  6. College of Communication and Information, University of Kentucky, Lexington, KY, USA

    Sherali Zeadally

  7. College of Technological Innovation, Zayed University, Dubai, United Arab Emirates

    Mohamad Badra

  8. University of Pisa, Pisa, Holy See (Vatican City State)

    Stefano Giordano

  9. DICIEAMA Department, University of Messina, Messina, Italy

    Maria Fazio

  10. CREATE-NET, Trento, Italy

    Andrey Somov

  11. University of Trento, Trento, Italy

    Radu-Laurentiu Vieriu

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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Abdelrahman, O.H., Gelenbe, E. (2016). A Data Plane Approach for Detecting Control Plane Anomalies in Mobile Networks. In: Mandler, B., et al. Internet of Things. IoT Infrastructures. IoT360 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 169. Springer, Cham. https://doi.org/10.1007/978-3-319-47063-4_19

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  • DOI: https://doi.org/10.1007/978-3-319-47063-4_19

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47062-7

  • Online ISBN: 978-3-319-47063-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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