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Sensors 2018, 18(6), 1691; https://doi.org/10.3390/s18061691

A Statistical Approach to Detect Jamming Attacks in Wireless Sensor Networks

1
Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Lynnwood Road, Pretoria 0002, South Africa
2
Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
*
Author to whom correspondence should be addressed.
Received: 27 April 2018 / Revised: 18 May 2018 / Accepted: 21 May 2018 / Published: 24 May 2018
(This article belongs to the Special Issue Smart Industrial Wireless Sensor Networks)
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Abstract

Wireless Sensor Networks (WSNs), in recent times, have become one of the most promising network solutions with a wide variety of applications in the areas of agriculture, environment, healthcare and the military. Notwithstanding these promising applications, sensor nodes in WSNs are vulnerable to different security attacks due to their deployment in hostile and unattended areas and their resource constraints. One of such attacks is the DoS jamming attack that interferes and disrupts the normal functions of sensor nodes in a WSN by emitting radio frequency signals to jam legitimate signals to cause a denial of service. In this work we propose a step-wise approach using a statistical process control technique to detect these attacks. We deploy an exponentially weighted moving average (EWMA) to detect anomalous changes in the intensity of a jamming attack event by using the packet inter-arrival feature of the received packets from the sensor nodes. Results obtained from a trace-driven simulation show that the proposed solution can efficiently and accurately detect jamming attacks in WSNs with little or no overhead. View Full-Text
Keywords: wireless sensor networks; jamming attack; exponentially weighted moving average; inter-arrival time wireless sensor networks; jamming attack; exponentially weighted moving average; inter-arrival time
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Osanaiye, O.; Alfa, A.S.; Hancke, G.P. A Statistical Approach to Detect Jamming Attacks in Wireless Sensor Networks. Sensors 2018, 18, 1691.

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