Abstract: In modern digital systems, ensuring data integrity and identity verification has become vital, particularly in areas like government records, legal documents, and banking. This paper presents a survey of a biometric watermarking system that combines iris and fingerprint traits to enhance authentication. The proposed approach uses a Rubik Cube- based encryption algorithm to secure extracted biometric features, which are then verified using Convolutional Neural Networks (CNNs). The objective is to embed the encrypted biometric information into host images, producing a watermark that is resistant to tampering and forgery. This paper reviews the underlying techniques, compares them with existing methods, and highlights the security and privacy advantages of the system. The study is further motivated by recent findings on the privacy risks of facial recognition systems, reinforcing the need for multi-modal, secure biometric authentication.
Keywords: Biometric Watermarking, Iris Recognition, Fingerprint Authentication, Rubik Encryption, CNN, Image Security, Multi-Modal Biometrics.
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DOI:
10.17148/IJARCCE.2025.14614
