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Efficient anonymous biometric matchi...

Luo, Ying.

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Efficient anonymous biometric matching in privacy-aware environments.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Efficient anonymous biometric matching in privacy-aware environments./
Author:	Luo, Ying.
Description:	140 p.
Notes:	Source: Dissertation Abstracts International, Volume: 76-01(E), Section: B.
Contained By:	Dissertation Abstracts International76-01B(E).
Subject:	Engineering, Computer. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3583957
ISBN:	9781321200294

Efficient anonymous biometric matching in privacy-aware environments.
Luo, Ying.

Efficient anonymous biometric matching in privacy-aware environments. - 140 p.

Source: Dissertation Abstracts International, Volume: 76-01(E), Section: B.

Thesis (Ph.D.)--University of Kentucky, 2014.

Video surveillance is an important tool used in security and environmental monitoring, however, the widespread deployment of surveillance cameras has raised serious privacy concerns. Many privacy-enhancing schemes have been recently proposed to automatically redact images of selected individuals in the surveillance video for protection. To identify these individuals for protection, the most reliable approach is to use biometric signals as they are immutable and highly discriminative. If misused, these characteristics of biometrics can seriously defeat the goal of privacy protection. In this dissertation, an Anonymous Biometric Access Control (ABAC) procedure is proposed based on biometric signals for privacy-aware video surveillance. The ABAC procedure uses Secure Multi-party Computational (SMC) based protocols to verify membership of an incoming individual without knowing his/her true identity. To make SMC-based protocols scalable to large biometric databases, I introduce the k-Anonymous Quantization (kAQ) framework to provide an effective and secure tradeoff of privacy and complexity. kAQ limits systems knowledge of the incoming individual to k maximally dissimilar candidates in the database, where k is a design parameter that controls the amount of complexity-privacy tradeoff. The relationship between biometric similarity and privacy is experimentally validated using a twin iris database. The effectiveness of the entire system is demonstrated based on a public iris biometric database.

ISBN: 9781321200294Subjects--Topical Terms:

1669061
Engineering, Computer.

Efficient anonymous biometric matching in privacy-aware environments.
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020 $a 9781321200294
035 $a (MiAaPQ)AAI3583957
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100 1 $a Luo, Ying. $3 1025170
245 1 0 $a Efficient anonymous biometric matching in privacy-aware environments.
300 $a 140 p.
500 $a Source: Dissertation Abstracts International, Volume: 76-01(E), Section: B.
500 $a Adviser: Sen-Ching S. Cheung.
502 $a Thesis (Ph.D.)--University of Kentucky, 2014.
520 $a Video surveillance is an important tool used in security and environmental monitoring, however, the widespread deployment of surveillance cameras has raised serious privacy concerns. Many privacy-enhancing schemes have been recently proposed to automatically redact images of selected individuals in the surveillance video for protection. To identify these individuals for protection, the most reliable approach is to use biometric signals as they are immutable and highly discriminative. If misused, these characteristics of biometrics can seriously defeat the goal of privacy protection. In this dissertation, an Anonymous Biometric Access Control (ABAC) procedure is proposed based on biometric signals for privacy-aware video surveillance. The ABAC procedure uses Secure Multi-party Computational (SMC) based protocols to verify membership of an incoming individual without knowing his/her true identity. To make SMC-based protocols scalable to large biometric databases, I introduce the k-Anonymous Quantization (kAQ) framework to provide an effective and secure tradeoff of privacy and complexity. kAQ limits systems knowledge of the incoming individual to k maximally dissimilar candidates in the database, where k is a design parameter that controls the amount of complexity-privacy tradeoff. The relationship between biometric similarity and privacy is experimentally validated using a twin iris database. The effectiveness of the entire system is demonstrated based on a public iris biometric database.
520 $a To provide the protected subjects with full access to their privacy information in video surveillance system, I develop a novel privacy information management system that allows subjects to access their information via the same biometric signals used for ABAC. The system is composed of two encrypted-domain protocols: the privacy information encryption protocol encrypts the original video records using the iris pattern acquired during ABAC procedure; the privacy information retrieval protocol allows the video records to be anonymously retrieved through a GC-based iris pattern matching process. Experimental results on a public iris biometric database demonstrate the validity of my framework.
520 $a KEYWORDS: Biometric Matching, Privacy, Authentication, Anonymity, Access Control.
590 $a School code: 0102.
650 4 $a Engineering, Computer. $3 1669061
650 4 $a Computer Science. $3 626642
650 4 $a Engineering, Electronics and Electrical. $3 626636
690 $a 0464
690 $a 0984
690 $a 0544
710 2 $a University of Kentucky. $b Electrical and Computer Engineering. $3 2103985
773 0 $t Dissertation Abstracts International $g 76-01B(E).
790 $a 0102
791 $a Ph.D.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3583957