Mr. Osama M. Ouda Profile

Osama M. Ouda

at Chiba Univ

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Proceedings Article | 17 May 2011 Paper

Security enhanced BioEncoding for protecting iris codes

Osama Ouda, Norimichi Tsumura, Toshiya Nakaguchi

Proceedings Volume 8029, 80291U (2011) https://doi.org/10.1117/12.883675

KEYWORDS: Iris, Biometrics, Iris recognition, Databases, Information security, Biological research, Resistance, Binary data, Computer security, Transform theory

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Improving the security of biometric template protection techniques is a key prerequisite for the widespread deployment of biometric technologies. BioEncoding is a recently proposed template protection scheme, based on the concept of cancelable biometrics, for protecting biometric templates represented as binary strings such as iris codes. The main advantage of BioEncoding over other template protection schemes is that it does not require user-specific keys and/or tokens during verification. Besides, it satisfies all the requirements of the cancelable biometrics construct without deteriorating the matching accuracy. However, although it has been shown that BioEncoding is secure enough against simple brute-force search attacks, the security of BioEncoded templates against more smart attacks, such as record multiplicity attacks, has not been sufficiently investigated. In this paper, a rigorous security analysis of BioEncoding is presented. Firstly, resistance of BioEncoded templates against brute-force attacks is revisited thoroughly. Secondly, we show that although the cancelable transformation employed in BioEncoding might be non-invertible for a single protected template, the original iris code could be inverted by correlating several templates used in different applications but created from the same iris. Accordingly, we propose an important modification to the BioEncoding transformation process in order to hinder attackers from exploiting this type of attacks. The effectiveness of adopting the suggested modification is validated and its impact on the matching accuracy is investigated empirically using CASIA-IrisV3-Interval dataset. Experimental results confirm the efficacy of the proposed approach and show that it preserves the matching accuracy of the unprotected iris recognition system.

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