Edwin Yang (University of Oklahoma) and Song Fang (University of Oklahoma)

With the advent of the in-vehicle infotainment (IVI) systems (e.g., Android Automotive) and other portable devices (e.g., smartphones) that may be brought into a vehicle, it becomes crucial to establish a secure channel between the vehicle and an in-vehicle device or between two in-vehicle devices. Traditional pairing schemes are tedious, as they require user interaction (e.g., manually typing in a passcode or bringing the two devices close to each other). Modern vehicles, together with smartphones and many emerging Internet-of-things (IoT) devices (e.g., dashcam) are often equipped with built-in Global Positioning System (GPS) receivers. In this paper, we propose a GPS-based Key establishment technique, called GPSKey, by leveraging the inherent randomness of vehicle movement. Specifically, vehicle movement changes with road ground conditions, traffic situations, and pedal operations. It thus may have rich randomness. Meanwhile, two in-vehicle GPS receivers can observe the same vehicle movement and exploit it for key establishment without requiring user interaction. We implement a prototype of GPSKey on top of off-the-shelf devices. Experimental results show that legitimate devices in the same vehicle require 1.18-minute of driving on average to establish a 128-bit key. Meanwhile, the attacker who follows or leads the victim’s vehicle is unable to infer the key.

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Shengwei An (Purdue University), Guanhong Tao (Purdue University), Qiuling Xu (Purdue University), Yingqi Liu (Purdue University), Guangyu Shen (Purdue University); Yuan Yao (Nanjing University), Jingwei Xu (Nanjing University), Xiangyu Zhang (Purdue University)

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Hiding My Real Self! Protecting Intellectual Property in Additive...

Sizhuang Liang (Georgia Institute of Technology), Saman Zonouz (Rutgers University), Raheem Beyah (Georgia Institute of Technology)

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V-Range: Enabling Secure Ranging in 5G Wireless Networks

Mridula Singh (CISPA - Helmholtz Center for Information Security), Marc Roeschlin (ETH Zurich), Aanjhan Ranganathan (Northeastern University), Srdjan Capkun (ETH Zurich)

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Demo #2: Sequential Attacks on Kalman Filter-Based Forward Collision...

Yuzhe Ma, Jon Sharp, Ruizhe Wang, Earlence Fernandes, and Jerry Zhu (University of Wisconsin–Madison)

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