Secret from muscle: Enabling secure pairing with electromyography

Lin Yang; Wei Wang; Qian Zhang

doi:10.1145/2994551.2994556

Secret from muscle: Enabling secure pairing with electromyography

Lin Yang, Wei Wang, Qian Zhang

Division of Integrative Systems and Design

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

44 Citations (Scopus)

Abstract

Forming secure pairing between wearable devices has become an important problem in many scenarios, such as mobile payments and private data transmission. This paper presents EMG-KEY, a system that can securely pair wearable devices by leveraging the electrical activity caused by human muscle contraction, that is, Electromyogram (EMG), to generate a secret key. Such a key can then be used by devices to authenticate each other's physical proximity and communicate confidentially. Extensive evaluation on 10 volunteers under different scenarios demonstrates that our system can achieve a competitive bit generation rate of 5.51 bit/s while maintaining a matching probability of 88.84%. Also, the evaluation results with the presence of adversaries demonstrate our system is secure to strong attackers who can eavesdrop on proximate wireless communication, capture and imitate legitimate pairing process with the help of camera.

Original language	English
Title of host publication	Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016
Publisher	Association for Computing Machinery, Inc
Pages	28-41
Number of pages	14
ISBN (Electronic)	9781450342636
DOIs	https://doi.org/10.1145/2994551.2994556
Publication status	Published - 14 Nov 2016
Event	14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016 - Stanford, United States Duration: 14 Nov 2016 → 16 Nov 2016

Publication series

Name	Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016

Conference

Conference	14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016
Country/Territory	United States
City	Stanford
Period	14/11/16 → 16/11/16

Bibliographical note

Publisher Copyright:
© 2016 Copyright held by the owner/author(s).

Keywords

EMG
Secret Key Generation
Secure Pairing

Access to Document

10.1145/2994551.2994556

Cite this

Yang, L., Wang, W., & Zhang, Q. (2016). Secret from muscle: Enabling secure pairing with electromyography. In Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016 (pp. 28-41). (Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016). Association for Computing Machinery, Inc. https://doi.org/10.1145/2994551.2994556

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Yang, L, Wang, W & Zhang, Q 2016, Secret from muscle: Enabling secure pairing with electromyography. in Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016. Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016, Association for Computing Machinery, Inc, pp. 28-41, 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016, Stanford, United States, 14/11/16. https://doi.org/10.1145/2994551.2994556

Secret from muscle: Enabling secure pairing with electromyography. / Yang, Lin; Wang, Wei; Zhang, Qian.
Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016. Association for Computing Machinery, Inc, 2016. p. 28-41 (Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

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Secret from muscle: Enabling secure pairing with electromyography

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Bibliographical note

Keywords

Access to Document

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