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Visual-Assisted Wormhole Attack Detection for Wireless Sensor Networks

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International Conference on Security and Privacy in Communication Networks (SecureComm 2014)

Abstract

Wireless sensor networks (WSNs) are gaining more and more interest in the research community due to their unique characteristics. In addition to energy consumption considerations, security has emerged as an equally important aspect in their network design. This is because WSNs are vulnerable to various types of attacks and to node compromises that threaten the security, integrity, and availability of data that resides in these networked systems. This paper develops a powerful, anomaly detection system that relies on visual analytics to monitor and promptly detect a particularly devastating form of attack, the wormhole attack. Wormhole attacks can severely deteriorate the network performance and compromise the security by disrupting the routing protocols. The proposed system, called VA-WAD, efficiently utilizes the routing dynamics to expose an adversary conducting a wormhole attack. Then, the output of the anomaly detection engine feeds the radial visualization engine of VA-WAD, which further assists the understanding and analysis of the network topology improving the detection accuracy. By employing an outer ring, VA-WAD also records the network security events occurring in the WSN on a 24 h basis. The obtained simulation results demonstrate the system’s visual and anomaly detection efficacy in exposing concurrent wormhole attacks.

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Acknowledgments

This work was performed within the framework of the Action “Supporting Postdoctoral Researchers” of the Operational Program “Education and Lifelong Learning” (Action’s Beneficiary: General Secretariat for Research and Technology), and is co-financed by the European Social Fund and the Greek State.

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Authors and Affiliations

  1. Interdepartmental Programme of Postgraduate Studies in Information Systems, University of Macedonia, Egnatia 156, Thessaloniki, Greece

    Eirini Karapistoli & Anastasios A. Economides

  2. Department of Informatics and Telecommunications Engineering, University of Western Macedonia, Karamanli and Ligeris Street, 50100, Kozani, Greece

    Panagiotis Sarigiannidis

Authors
  1. Eirini Karapistoli
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  2. Panagiotis Sarigiannidis
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  3. Anastasios A. Economides
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Corresponding author

Correspondence to Eirini Karapistoli .

Editor information

Editors and Affiliations

  1. CAS, Institute of Information Engineering CAS, Beijing, China

    Jing Tian

  2. Institute of Information Engineering, CAS, Beijing, China

    Jiwu Jing

  3. IBM Thomas J. Watson Research Center, New York, New York, USA

    Mudhakar Srivatsa

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© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Karapistoli, E., Sarigiannidis, P., Economides, A.A. (2015). Visual-Assisted Wormhole Attack Detection for Wireless Sensor Networks. In: Tian, J., Jing, J., Srivatsa, M. (eds) International Conference on Security and Privacy in Communication Networks. SecureComm 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 152. Springer, Cham. https://doi.org/10.1007/978-3-319-23829-6_17

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  • DOI: https://doi.org/10.1007/978-3-319-23829-6_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23828-9

  • Online ISBN: 978-3-319-23829-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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