Analysis of reflexive eye movements for fast replay-resistant biometric authentication
- Submitting institution
-
University of Oxford
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2065
- Type
- D - Journal article
- DOI
-
10.1145/3281745
- Title of journal
- ACM Transactions on Privacy and Security
- Article number
- 4
- First page
- 1
- Volume
- 22
- Issue
- 1
- ISSN
- 2471-2566
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This article, which extends a conference version at ACM CCS�16, describes the design, implementation, and evaluation of a biometrics authentication system based on reflexive eye movements. This type of eye movement is captured at the millisecond-scale and enables fast authentication and resilience against replay attacks, while minimising users� cognitive effort. The work is part of a larger research collaboration on biometric authentication for financial services with Mastercard, who have donated �400k to support the work since 2016. It is part of the research basis for the Oxford spinout phishAR (www.phishar.com), itself part of Mastercard�s startup engagement programme Start Path.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -