Document Type

Conference Proceeding

Publication Date

7-2020

Publication Title

WiSec '20: Proceedings of the 13th ACM Conference on Security and Privacy in Wireless and Mobile Networks

Pages

25-30

Publisher Name

Association for Computing Machinery

Abstract

The emergence of advanced in-vehicle infotainment (IVI) systems, such as Apple CarPlay and Android Auto, calls for fast and intuitive device pairing mechanisms to discover newly introduced devices and make or break a secure, high-bandwidth wireless connection. Current pairing schemes are tedious and lengthy as they typically require users to go through pairing and verification procedures by manually entering a predetermined or randomly generated pin on both devices. This inconvenience usually results in prolonged usage of old pins, significantly degrading the security of network connections.

To address this challenge, we propose ivPair, a secure and usable device pairing protocol that extracts an identical pairing pin or fingerprint from vehicle's vibration response caused by various factors such as driver's driving pattern, vehicle type, and road conditions. Using ivPair, users can pair a mobile device equipped with an accelerometer with the vehicle's IVI system or other mobile devices by simply holding it against the vehicle's interior frame. Under realistic driving experiments with various types of vehicles and road conditions, we demonstrate that all passenger-owned devices can expect a high pairing success rate with a short pairing time, while effectively rejecting proximate adversaries attempting to pair with the target vehicle.

Comments

Author Posting © Association for Computing Machinery, 2020. This is the author's version of the work. It is posted here by permission of Association for Computing Machinery for personal use, not for redistribution. The definitive version was published in WiSec '20: Proceedings of the 13th ACM Conference on Security and Privacy in Wireless and Mobile Networks, July 2020. https://doi.org/10.1145/3395351.3399436

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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