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VCLT: An accurate trajectory tracking attack based on crowdsourcing in VANETs

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Indexed by:会议论文

Date of Publication:2015-11-18

Included Journals:EI、Scopus

Volume:9530

Page Number:297-310

Abstract:We investigate trajectory tracking in Vehicular Ad hoc Networks (VANETs) in this work. Previous tracking methods suffer from low accuracy, large overhead, and big error. In this paper, we propose a Vehicular Crowdsourcing Localization and Tracking (VCLT) scheme for mounting a trajectory tracking attack. In our scheme, crowdsourcing technique is applied to sample the location information of certain users. Then matrix completion algorithm is used to generate our predictions of the users   trajectories. To alleviate the error disturbance of the recovered location data, Kalman filter technique is implemented and the trajectories of certain users are recovered with accuracy. At last, extensive simulations are conducted to show the performance of our scheme. Simulations results reveal that the proposed approach is able to accurately track the trajectories of certain users. ? Springer International Publishing Switzerland 2015.

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