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Journal article

Pulse-response: Exploring human body impedance for biometric recognition

Abstract:
Biometric characteristics are often used as a supplementary component in user authentication and identification schemes. Many biometric traits, both physiological and behavioral, offering a wider range of security and stability, have been explored. We propose a new physiological trait based on the human body’s electrical response to a square pulse signal, called pulse-response, and analyze how this biometric characteristic can be used to enhance security in the context of two example applications: (1) an additional authentication mechanism in PIN entry systems and (2) a means of continuous authentication on a secure terminal. The pulse-response biometric recognition is effective because each human body exhibits a unique response to a signal pulse applied at the palm of one hand and measured at the palm of the other. This identification mechanism integrates well with other established methods and could offer an additional layer of security, either on a continuous basis or at log-in time.We build a proof-of-concept prototype and perform experiments to assess the feasibility of pulse-response for biometric authentication. The results are very encouraging, achieving an equal error rate of 2% over a static dataset and 9% over a dataset with samples taken over several weeks. We also quantize resistance to attack by estimating individual worst-case probabilities for zero-effort impersonation in different experiments.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1145/3064645

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Oxford college:
Kellogg College
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Role:
Author


Publisher:
Association for Computing Machinery
Journal:
ACM Transactions on Privacy and Security More from this journal
Volume:
20
Issue:
2
Pages:
1-31
Publication date:
2017-05-28
Acceptance date:
2017-03-01
DOI:
EISSN:
2471-2574
ISSN:
2471-2566


Keywords:
Pubs id:
pubs:719566
UUID:
uuid:0fe5e296-cd89-47a7-afc0-c87905b190cb
Local pid:
pubs:719566
Source identifiers:
719566
Deposit date:
2018-04-30

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