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

  • Authors:
  • Paul Dunphy;Andreas P. Heiner;N. Asokan

  • Affiliations:
  • Newcastle University, Newcastle upon-Tyne, UK;Nokia Research Center, Helsinki, Finland;Nokia Research Center, Helsinki, Finland

  • Venue:
  • Proceedings of the Sixth Symposium on Usable Privacy and Security
  • Year:
  • 2010

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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.