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Future Internet 2016, 8(1), 2;

Detection of Intelligent Intruders in Wireless Sensor Networks

Department of Computer Science and Information Systems, Bradley University, 1501 W Bradley Ave, Peoria, IL 61625, USA
Author to whom correspondence should be addressed.
Academic Editors: Xiaolong Li, Shaoen Wu and Jose Ignacio Moreno Novella
Received: 31 July 2015 / Revised: 27 November 2015 / Accepted: 7 December 2015 / Published: 20 January 2016
(This article belongs to the Special Issue Internet of Things)
Full-Text   |   PDF [3181 KB, uploaded 20 January 2016]   |  


Most of the existing research works on the intrusion detection problem in a wireless sensor network (WSN) assume linear or random mobility patterns in abstracting intruders’ models in traversing the WSN field. However, in real-life WSN applications, an intruder is usually an intelligent mobile robot with environment learning and detection avoidance capability (i.e., the capability to avoid surrounding sensors). Due to this, the literature results based on the linear or random mobility models may not be applied to the real-life WSN design and deployment for efficient and effective intrusion detection in practice. This motivates us to investigate the impact of intruder’s intelligence on the intrusion detection problem in a WSN for various applications. To be specific, we propose two intrusion algorithms, the pinball and flood-fill algorithms, to mimic the intelligent motion and behaviors of a mobile intruder in detecting and circumventing nearby sensors for detection avoidance while heading for its destination. The two proposed algorithms are integrated into a WSN framework for intrusion detection analysis in various circumstances. Monte Carlo simulations are conducted, and the results indicate that: (1) the performance of a WSN drastically changes as a result of the intruder’s intelligence in avoiding sensor detections and intrusion algorithms; (2) network parameters, including node density, sensing range and communication range, play a crucial part in the effectiveness of the intruder’s intrusion algorithms; and (3) it is imperative to integrate intruder’s intelligence in the WSN research for intruder detection problems under various application circumstances. View Full-Text
Keywords: artificial intelligence; intrusion detection; mobile intruder; performance evaluation; simulation; wireless sensor networks artificial intelligence; intrusion detection; mobile intruder; performance evaluation; simulation; wireless sensor networks

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Wang, Y.; Chu, W.; Fields, S.; Heinemann, C.; Reiter, Z. Detection of Intelligent Intruders in Wireless Sensor Networks. Future Internet 2016, 8, 2.

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