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Sensors 2018, 18(2), 638;

Sensor Compromise Detection in Multiple-Target Tracking Systems

Department of Electronics Engineering, University of Guanajuato, Salamanca, Gto. 36885, Mexico
Munitions Directorate, Air Force Research Laboratory, Eglin AFB, FL 32542, USA
Author to whom correspondence should be addressed.
Received: 30 December 2017 / Revised: 14 February 2018 / Accepted: 17 February 2018 / Published: 21 February 2018
(This article belongs to the Special Issue Security, Trust and Privacy for Sensor Networks)
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Tracking multiple targets using a single estimator is a problem that is commonly approached within a trusted framework. There are many weaknesses that an adversary can exploit if it gains control over the sensors. Because the number of targets that the estimator has to track is not known with anticipation, an adversary could cause a loss of information or a degradation in the tracking precision. Other concerns include the introduction of false targets, which would result in a waste of computational and material resources, depending on the application. In this work, we study the problem of detecting compromised or faulty sensors in a multiple-target tracker, starting with the single-sensor case and then considering the multiple-sensor scenario. We propose an algorithm to detect a variety of attacks in the multiple-sensor case, via the application of finite set statistics (FISST), one-class classifiers and hypothesis testing using nonparametric techniques. View Full-Text
Keywords: sensor networks; estimation; cyberphysical systems sensor networks; estimation; cyberphysical systems

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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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Ramirez-Paredes, J.-P.; Doucette, E.A.; Curtis, J.W.; Ayala-Ramirez, V. Sensor Compromise Detection in Multiple-Target Tracking Systems. Sensors 2018, 18, 638.

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