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Fingerprint-PKI authentication using Zernike moments

Authors: Han-Ul Jang; Dai-Kyung Hyun; Dae-Jin Jung; Heung-Kyu Lee;

Fingerprint-PKI authentication using Zernike moments

Abstract

Bio-cryptographic systems provide security by securing a cryptographic key with biometric data. To secure the cryptographic key, biometric data should be significantly consistent. However, the uncertainty of biometrics makes it complicated to achieve highly accurate authentication. In this paper, we propose a novel bio-cryptographic authentication scheme that improves the security of Public Key Infrastructure. To confirm authenticity of a public key and make authentication information using biometric features consistent, we created a one-way, bio-hash function by using a public-key bitstream and Zernike moments extracted from fingerprint images. Experimental results and analysis show that the proposed method prevents attackers from modifying public-key certificates and getting access to biometric data. Moreover, the results prove that the proposed method achieves very high accuracy.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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