A Robust Multimodel Biometric Crypto System
Komal1, Chander Kant2

1Komal, Ph.D Scholar, Department of Computer Science and Application, KUK, (Haryana), India.
2Dr. Chander Kant, Assistant Professor, Department of Computer Science and Application, KUK, (Haryana), India.
Manuscript received on 25 August 2019 | Revised Manuscript received on 11 September 2019 | Manuscript Published on 17 September 2019 | PP: 1953-1961 | Volume-8 Issue-2S8 August 2019 | Retrieval Number: B12060882S819/2019©BEIESP | DOI: 10.35940/ijrte.B1206.0882S819
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Biometric based authentication has several advantages over traditional password or PIN based authentication process because biometric is consists of physical or behavioural characteristics i.e fingerprint, face, Finger Knuckle Print (FKP), iris, voice etc. Unimodal biometric system h as some drawbacks i.e non universality, inter-class variation, intra-class variation; system can be circumvented by the skilled imposter etc. These drawbacks can overcome by multimodal biometric system as it combines more than one modality for authentication. When multimodal system combined with cryptography it makes system more robust and secure. In this paper, a robust multimodal biometric crypto system has been proposed, in which two modalities (FKP and face) are used for authentication of a person and one modality (fingerprint) is used for key generation. AES algorithm with fingerprint based key is used for securing the biometric templates. At authentication time, decision level fusion with AND rule is used for making the final decision. The proposed multimodal biometric crypto system is more robust and secure as compare with other multimodal biometric systems. Experimental results are shown with the help of MATLAB3. 2017b.
Keywords: Biometric Crypto System; Face Recognition; Finger Recognition; FKP Recognition; Multimodal Biometric System.
Scope of the Article: Image Processing and Pattern Recognition