Research Article
Visual-Assisted Wormhole Attack Detection for Wireless Sensor Networks
@INPROCEEDINGS{10.1007/978-3-319-23829-6_17, author={Eirini Karapistoli and Panagiotis Sarigiannidis and Anastasios Economides}, title={Visual-Assisted Wormhole Attack Detection for Wireless Sensor Networks}, proceedings={International Conference on Security and Privacy in Communication Networks. 10th International ICST Conference, SecureComm 2014, Beijing, China, September 24-26, 2014, Revised Selected Papers, Part I}, proceedings_a={SECURECOMM}, year={2015}, month={11}, keywords={Wireless sensor networks Wormhole attacks Anomaly detection Security visualization}, doi={10.1007/978-3-319-23829-6_17} }- Eirini Karapistoli
Panagiotis Sarigiannidis
Anastasios Economides
Year: 2015
Visual-Assisted Wormhole Attack Detection for Wireless Sensor Networks
SECURECOMM
Springer
DOI: 10.1007/978-3-319-23829-6_17
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 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.
