Title
Privacy-Preserving Biometric Identification Using Secure Multiparty Computation: An Overview and Recent Trends
Abstract
This article presents a tutorial overview of the application of techniques of secure two-party computation (also known as secure function evaluation) to biometric identification. These techniques enable to compute biometric identification algorithms while maintaining the privacy of the biometric data. This overview considers the main tools of secure two-party computations such as homomorphic encryption, garbled circuits (GCs), and oblivious transfers (OTs) and intends to give clues on the best practices to secure a biometric identification protocol. It also presents recent trends in privacy-preserving biometric identification that aim at making it usable in real-life applications.
Year
DOI
Venue
2013
10.1109/MSP.2012.2230218
Signal Processing Magazine, IEEE
Keywords
Field
DocType
biometrics (access control),cryptographic protocols,data privacy,image recognition,GC,OT,biometric data privacy,biometric identification protocol,garbled circuits,homomorphic encryption,oblivious transfer,privacy-preserving biometric identification,secure function evaluation,secure multiparty computation,secure two-party computation
USable,Homomorphic encryption,Secure multi-party computation,Cryptographic protocol,Computer security,Computer science,Theoretical computer science,Biometric data,Biometrics,Secure two-party computation,Information privacy
Journal
Volume
Issue
ISSN
30
2
1053-5888
Citations 
PageRank 
References 
31
0.91
17
Authors
3
Name
Order
Citations
PageRank
Julien Bringer1381.80
Hervé Chabanne2311.59
Alain Patey31288.02