DocumentCode :
3650732
Title :
Define privacy-preserving setbase drawer size standard: A ∊-closeness perspective
Author :
Benjamin Justus;Frédéric Cuppens;Nora Cuppens-Boulahia;Julien Bringer;Herve Chabanne;Olivier Cipiere
Author_Institution :
Lab-STICC, Té
fYear :
2013
Firstpage :
362
Lastpage :
365
Abstract :
Shamir proposed the setbase approach as a means of improving security and privacy of the traditional biometric system. As a result of the limitation of the current setbase filling procedure, we demonstrate that there are potential privacy weaknesses due to non-default distributions on attributes inside the identity database. We introduce in this paper, the concept of ϵ-closeness as a general framework to describe quantitatively the distribution anomaly. As a consequence, we are able to formulate a privacy-preserving drawer size standard for the setbase that includes the non-default distribution cases.
Keywords :
"Databases","Standards","Data privacy","Privacy","Handheld computers","Security","Measurement"
Publisher :
ieee
Conference_Titel :
Privacy, Security and Trust (PST), 2013 Eleventh Annual International Conference on
Type :
conf
DOI :
10.1109/PST.2013.6596090
Filename :
6596090
Link To Document :
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