Josef Küng, Thi Thuy Linh Vo, Tran Khanh Dang,
"A Hash-Based Index Method for Securing Biometric Fuzzy Vaults"
: Trust, Privacy, and Security in Digital Business, Serie Lecture Notes in Computer Science (LNCS), Vol. 8647, Springer, Berlin, Heidelberg, Seite(n) 60-71, 11-2014
Original Titel:
A Hash-Based Index Method for Securing Biometric Fuzzy Vaults
Sprache des Titels:
Deutsch
Original Buchtitel:
Trust, Privacy, and Security in Digital Business
Englische Kurzfassung:
Traditional cryptography helps to protect information and establish secure interactions by using a cryptographic key to encode/decode user secret data. The problem related to managing such keys has gained much attention from the research as well as commercial communities, but there exists many security concerns that are still open. Such limitations can be solved by Biometric Cryptosystems (BCSs). We propose a method to help increasing the security level of one of the most popular key-binding BCSs: Fuzzy Vault. We remove x-coordinates out of the vault while indexing y-coordinates by evaluation of corresponding x-coordinate values based on a suitable hash function. We carry out experiments on a Fuzzy Vault scheme based on iriscode. Our method has increased the min-entropy to 52 bits (it was 40 bits in the original scheme) and reduced the size of the vault dramatically. The proposed method also helps to prevent attacks via record multiplicity and stolen key attacks.
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