NDLI: An Analysis of Random Projection for Changeable and Privacy-Preserving Biometric Verification

Content Provider	IEEE Xplore Digital Library
Author	Yongjin Wang Plataniotis, K.N.
Copyright Year	1996
Abstract	Changeability and privacy protection are important factors for widespread deployment of biometrics-based verification systems. This paper presents a systematic analysis of a random-projection (RP)-based method for addressing these problems. The employed method transforms biometric data using a random matrix with each entry an independent and identically distributed Gaussian random variable. The similarity- and privacy-preserving properties, as well as the changeability of the biometric information in the transformed domain, are analyzed in detail. Specifically, RP on both high-dimensional image vectors and dimensionality-reduced feature vectors is discussed and compared. A vector translation method is proposed to improve the changeability of the generated templates. The feasibility of the introduced solution is well supported by detailed theoretical analyses. Extensive experimentation on a face-based biometric verification problem shows the effectiveness of the proposed method.
Page Count	14
File Size	714202
Starting Page	1280
Ending Page	1293
File Format	PDF
ISSN	10834419
Volume Number	40
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biometrics Privacy Bioinformatics Data mining Protection Random variables Information analysis Face recognition Security Spatial databases random projection (RP) changeability face recognition privacy
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Information Systems Electrical and Electronic Engineering Human-Computer Interaction Computer Science Applications Software

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