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Glass Unlock: Enhancing Security of Smartphone Unlocking through Leveraging a Private Near-eye Display

Published:18 April 2015Publication History

ABSTRACT

This paper presents Glass Unlock, a novel concept using smart glasses for smartphone unlocking, which is theoretically secure against smudge attacks, shoulder-surfing, and camera attacks. By introducing an additional temporary secret like the layout of digits that is only shown on the private near-eye display, attackers cannot make sense of the observed input on the almost empty phone screen. We report a user study with three alternative input methods and compare them to current state-of-the-art systems. Our findings show that Glass Unlock only moderately increases authentication times and that users favor the input method yielding the slowest input times as it avoids focus switches between displays.

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References

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  1. Glass Unlock: Enhancing Security of Smartphone Unlocking through Leveraging a Private Near-eye Display

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    • Published in

      cover image ACM Conferences
      CHI '15: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems
      April 2015
      4290 pages
      ISBN:9781450331456
      DOI:10.1145/2702123

      Copyright © 2015 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      New York, NY, United States

      Publication History

      • Published: 18 April 2015

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      Acceptance Rates

      CHI '15 Paper Acceptance Rate486of2,120submissions,23%Overall Acceptance Rate6,199of26,314submissions,24%

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