| dc.description.abstract | Biometric authentication systems have gained immense popularity due to theirability to provide secure and convenient authentication. However, the leakageof sensitive biometric data can compromise an individual�s privacy and security.To address this issue, a privacy-preserving biometric authentication system basedon iris data is proposed in this paper. The framework exploits the homomorphicproperties to process encrypted data, thereby ensuring the privacy of sensitivedata, even while using the services of third-party cloud service providers (CSPs).In the initial stage of the experiment, we encrypt the data, and comparison wasdone by using hamming distance, but after completion of the first experiment,we realized that data can be morphed through an insecure channel by using multipleattacks to overcome this we have proposed framework were morphing isperformed on the iris data by using a man-in-the-middle attack. Two iris identificationAlgorithms are proposed, with a success rate of over 60% and a false matchrate of 5%, and are vulnerable to morph attacks. We also examine how comparablethe original and morphed iris images must be. Using original images, we presentour findings for morphing iris detection. The proposed privacy-preserving biometricauthentication system offers a robust framework that minimizes time complexitycompared to other state-of-the-art approaches. This framework ensuresthe privacy of sensitive data and provides a secure biometric authentication system. | |
