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A closer look at recognition-based graphical passwords on mobile devices

Lookup NU author(s): Dr Paul Dunphy

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Abstract

Graphical password systems based on the recognition of photographs are candidates to alleviate current over-reliance on alphanumeric passwords and PINs. However, despite being based on a simple concept - and user evaluations consistently reporting impressive memory retention - only one commercial example exists and overall take-up is low. Barriers to uptake include a perceived vulnerability to observation attacks; issues regarding deployability; and the impact of innocuous design decisions on security not being formalized. Our contribution is to dissect each of these issues in the context of mobile devices - a particularly suitable application domain due to their increasing significance, and high potential to attract unauthorized access. This produces: 1) A novel yet simple solution to the intersection attack that permits greater variability in login challenges; 2) Detailed analysis of the shoulder surfing threat that considers both simulated and human testing; 3) A first look at image processing techniques to contribute towards automated photograph filtering. We operationalize our observations and gather data in a field context where decentralized mechanisms of varying entropy were installed on the personal devices of participants. Across two working weeks success rates collected from users of a high entropy version were similar to those of a low entropy version at 77%, and login durations decreased significantly across the study. © 2010 ACM.


Publication metadata

Author(s): Dunphy P, Heiner A, Asokan N

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Proceedings of the Sixth Symposium on Usable Privacy and Security

Year of Conference: 2010

Pages: -

Publisher: ACM Press

URL: http://dx.doi.org/10.1145/1837110.1837114

DOI: 10.1145/1837110.1837114

Library holdings: Search Newcastle University Library for this item

ISBN: 9781450302647


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