Side-channel inference attacks on mobile keypads using smartwatches

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Authors
Maiti, Anindya
Jadliwala, Murtuza Shabbir
He, Jibo
Bilogrevic, Igor
Advisors
Issue Date
2018-09-01
Type
Article
Keywords
Wearables , Smartwatches , Side channel attacks , Keystroke inference
Research Projects
Organizational Units
Journal Issue
Citation
A. Maiti, M. Jadliwala, J. He and I. Bilogrevic, "Side-Channel Inference Attacks on Mobile Keypads Using Smartwatches," in IEEE Transactions on Mobile Computing, vol. 17, no. 9, pp. 2180-2194, 1 Sept. 2018
Abstract

Smartwatches enable many novel applications and are fast gaining popularity. However, the presence of a diverse set of onboard sensors provides an additional attack surface to malicious software and services on these devices. In this paper, we investigate the feasibility of key press inference attacks on handheld numeric touchpads by using smartwatch motion sensors as a side-channel. We consider different typing scenarios, and propose multiple attack approaches to exploit the characteristics of the observed wrist movements for inferring individual key presses. Experimental evaluation using commercial off-the-shelf smartwatches and smartphones show that key press inference using smartwatch motion sensors is not only fairly accurate, but also comparable with similar attacks using smartphone motion sensors. Additionally, hand movements captured by a combination of both smartwatch and smartphone motion sensors yields better inference accuracy than either device considered individually.

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Publisher
IEEE
Journal
Book Title
Series
IEEE Transactions on Mobile Computing;v.17:no.9
PubMed ID
DOI
ISSN
1536-1233
EISSN