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Gait-Key: A Gait-Based Shared Secret Key Generation Protocol for Wearable Devices

Published:26 January 2017Publication History
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Abstract

Recent years have witnessed a remarkable growth in the number of smart wearable devices. For many of these devices, an important security issue is to establish an authenticated communication channel between legitimate devices to protect the subsequent communications. Due to the wireless nature of the communication and the extreme resource constraints of sensor devices, providing secure, efficient, and user-friendly device pairing is a challenging task. Traditional solutions for device pairing mostly depend on key predistribution, which is unsuitable for wearable devices in many ways. In this article, we design Gait-Key, a shared secret key generation scheme that allows two legitimate devices to establish a common cryptographic key by exploiting users’ walking characteristics (gait). The intuition is that the sensors on different locations on the same body experience similar accelerometer signals when the user is walking. However, one main challenge is that the accelerometer also captures motion signals produced by other body parts (e.g., swinging arms). We address this issue by using the blind source separation technique to extract the informative signal produced by the unique gait patterns. Our experimental results show that Gait-Key can generate a common 128-bit key for two legitimate devices with 98.3% probability. To demonstrate the feasibility, the proposed key generation scheme is implemented on modern smartphones. The evaluation results show that the proposed scheme can run in real time on modern mobile devices and incurs low system overhead.

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      • Published in

        cover image ACM Transactions on Sensor Networks
        ACM Transactions on Sensor Networks  Volume 13, Issue 1
        February 2017
        242 pages
        ISSN:1550-4859
        EISSN:1550-4867
        DOI:10.1145/3027492
        • Editor:
        • Chenyang Lu
        Issue’s Table of Contents

        Copyright © 2017 ACM

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        Publication History

        • Published: 26 January 2017
        • Accepted: 1 November 2016
        • Revised: 1 October 2016
        • Received: 1 July 2016
        Published in tosn Volume 13, Issue 1

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