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Reducing shoulder-surfing by using gaze-based password entry
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ACM International Conference Proceeding Series; Vol. 229 archive
Proceedings of the 3rd symposium on Usable privacy and security table of contents
Pittsburgh, Pennsylvania
SESSION: Passwords table of contents
Pages: 13 - 19  
Year of Publication: 2007
ISBN:978-1-59593-801-5
Authors
Manu Kumar  Stanford University, Stanford, CA
Tal Garfinkel  Stanford University, Stanford, CA
Dan Boneh  Stanford University, Stanford, CA
Terry Winograd  Stanford University, Stanford, CA
Sponsor
: CyLab
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 25,   Downloads (12 Months): 155,   Citation Count: 7
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ABSTRACT

Shoulder-surfing -- using direct observation techniques, such as looking over someone's shoulder, to get passwords, PINs and other sensitive personal information -- is a problem that has been difficult to overcome. When a user enters information using a keyboard, mouse, touch screen or any traditional input device, a malicious observer may be able to acquire the user's password credentials. We present EyePassword, a system that mitigates the issues of shoulder surfing via a novel approach to user input.

With EyePassword, a user enters sensitive input (password, PIN, etc.) by selecting from an on-screen keyboard using only the orientation of their pupils (i.e. the position of their gaze on screen), making eavesdropping by a malicious observer largely impractical. We present a number of design choices and discuss their effect on usability and security. We conducted user studies to evaluate the speed, accuracy and user acceptance of our approach. Our results demonstrate that gaze-based password entry requires marginal additional time over using a keyboard, error rates are similar to those of using a keyboard and subjects preferred the gaze-based password entry approach over traditional methods.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  7

Collaborative Colleagues:
Manu Kumar: colleagues
Tal Garfinkel: colleagues
Dan Boneh: colleagues
Terry Winograd: colleagues