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Artificial Intelligence Review

Erschienen in:

09.10.2019

Cancelable Biometrics: a comprehensive survey

verfasst von: Manisha, Nitin Kumar

Erschienen in: Artificial Intelligence Review | Ausgabe 5/2020

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Abstract

Biometric recognition is a challenging research field but suffers from privacy and security concerns. To address this concern, Cancelable Biometrics is suggested in literature in which a Biometric image of a sample is distorted or transformed in such a manner that it becomes difficult to obtain the original Biometric image from the distorted one. Another important characteristic of Cancelable Biometrics is that it can be reissued if compromised. In this research paper, we present a comprehensive survey of more than 120 techniques suggested by various researchers from time to time for Cancelable Biometrics and a novel taxonomy for the same is developed. Further, various performance measures used in Cancelable Biometrics are reviewed and their mathematical formulations are given. Cancelable Biometrics also suffer from various security attacks as given in literature. A review of these security attacks is carried out. We have also performed a review of databases used in literature for nine different Cancelable Biometrics viz. Face, Iris, Speech, Fingerprint, Signature, Palmprint, ECG, Palmvein and Fingervein. Lastly, we have also given future research directions in this field. This study shall be useful for the researchers and practitioners working in this fascinating research area.

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Titel: Cancelable Biometrics: a comprehensive survey
verfasst von: Manisha
Nitin Kumar
Publikationsdatum: 09.10.2019
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 5/2020
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-019-09767-8

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