Visible to the public Biblio

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2019-05-20
Wang, Ge, Qian, Chen, Cai, Haofan, Han, Jinsong, Zhao, Jizhong.  2018.  Replay-resilient Authentication for IoT. Proceedings of the 10th on Wireless of the Students, by the Students, and for the Students Workshop. :3–5.

We provide the first solution to an important question, "how a physical-layer RFID authentication method can defend against signal replay attacks". It was believed that if the attacker has a device that can replay the exact same reply signal of a legitimate tag, any physical-layer authentication method will fail. This paper presents Hu-Fu, the first physical layer RFID authentication protocol that is resilient to the major attacks including tag counterfeiting, signal replay, signal compensation, and brute-force feature reply. Hu-Fu is built on two fundamental ideas, namely inductive coupling of two tags and signal randomization. Hu-Fu does not require any hardware or protocol modification on COTS passive tags and can be implemented with COTS devices. We implement a prototype of Hu-Fu and demonstrate that it is accurate and robust to device diversity and environmental changes.

2018-05-16
Wang, Ge, Qian, Chen, Cai, Haofan, Han, Jinsong, Ding, Han, Zhao, Jizhong.  2017.  Replay-resilient Physical-layer Authentication for Battery-free IoT Devices. Proceedings of the 4th ACM Workshop on Hot Topics in Wireless. :7–11.

On battery-free IoT devices such as passive RFID tags, it is extremely difficult, if not impossible, to run cryptographic algorithms. Hence physical-layer identification methods are proposed to validate the authenticity of passive tags. However no existing physical-layer authentication method of RFID tags that can defend against the signal replay attack. This paper presents Hu-Fu, a new direction and the first solution of physical layer authentication that is resilient to the signal replay attack, based on the fact of inductive coupling of two adjacent tags. We present the theoretical model and system workflow. Experiments based on our implementation using commodity devices show that Hu-Fu is effective for physical-layer authentication.

2017-08-22
Ding, Han, Qian, Chen, Han, Jinsong, Wang, Ge, Jiang, Zhiping, Zhao, Jizhong, Xi, Wei.  2016.  Device-free Detection of Approach and Departure Behaviors Using Backscatter Communication. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. :167–177.

Smart environments and security systems require automatic detection of human behaviors including approaching to or departing from an object. Existing human motion detection systems usually require human beings to carry special devices, which limits their applications. In this paper, we present a system called APID to detect arm reaching by analyzing backscatter communication signals from a passive RFID tag on the object. APID does not require human beings to carry any device. The idea is based on the influence of human movements to the vibration of backscattered tag signals. APID is compatible with commodity off-the-shelf devices and the EPCglobal Class-1 Generation-2 protocol. In APID an commercial RFID reader continuously queries tags through emitting RF signals and tags simply respond with their IDs. A USRP monitor passively analyzes the communication signals and reports the approach and departure behaviors. We have implemented the APID system for both single-object and multi-object scenarios in both horizontal and vertical deployment modes. The experimental results show that APID can achieve high detection accuracy.