Abstract
Nowadays, Radio Frequency Identification (RFID) has become one of the most deployed Internet of Things (IoT) technologies. The security threats it facing are gaining more and more attention. In this paper, we focus on the intrusion based on unauthorized (malicious) readers by catching the information of tags and modifying the tags via a standard protocol. We design URTracker to realize the detection and localization of unauthorized readers. This system has two parts: For detection, we analyze the features of reader interference and the RFID signal channel model and propose a throughput-based method. For localization, we use the relationship between throughput and the position as fingerprints, model the localization process into a Markov Decision Process (MDP) for training via deep reinforcement learning (DRL). Experiment results show that URTracker can achieve high accuracy to detect unauthorized readers and low location error for tracking the trajectories.
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Acknowledgement
This work was supported by the Youth Innovation Promotion Association of Chinese Academy of Sciences, No. Y9YY015104.
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Sun, D., Cui, Y., Feng, Y., Xie, J., Wang, S., Zhang, Y. (2021). URTracker: Unauthorized Reader Detection and Localization Using COTS RFID. In: Liu, Z., Wu, F., Das, S.K. (eds) Wireless Algorithms, Systems, and Applications. WASA 2021. Lecture Notes in Computer Science(), vol 12937. Springer, Cham. https://doi.org/10.1007/978-3-030-85928-2_27
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DOI: https://doi.org/10.1007/978-3-030-85928-2_27
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