Security and Privacy in Biometric Authentication: Advancements and Risks Across Platforms
subject: Biometric authentication; Face recognition; Fingerprint recognition; Iris recognition; Privacy and security
description: Biometric identification systems like fingerprint, face, iris, and voice recognition have revolutionized user authentication with more convenience and increased security over conventional password based authentication. Nonetheless, the fact that biometric features are immutable introduces unprecedented issues around privacy, spoofing, and database compromise because once biometric data leaks out, it cannot be withdrawn or substituted. This work advances empirical testing with analytical analysis to test biometric authentication for face, fingerprint, and iris modalities. Models based on convolutional neural networks (CNNs) were used and evaluated on benchmarked datasets, and findings indicated that face and iris recognition performed nearly perfectly with zero false acceptance and rejection rates in controlled environments, while fingerprint recognition performed poorly because of dataset size and quality constraints. The conclusions identify the significance of data preparation and variation in ascertaining the reliability of biometric information. In an effort to cross-verify the experiments further, case studies of Aadhaar, Apple Face ID, and Biostar 2 also clarified the threats of central storage, spoofing, and regulatory loopholes. The research concludes by suggesting privacy preserving frameworks, encryption, and multimodal methods for securing the future of biometric authentication. 2025 IEEE.
creator: Benny, Sandra; Das, Deepthi; Rajesh Kanna, R.
source: Proceedings - 2025 International Conference on Transformative Computing Technologies, ICTCT 2025;pp.254-259
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 979-833159195-3;
language: English
type: Conference paper
coverage: Benny S., Christ University Computer Science, Bengaluru, India; Das D., Christ University Statistics and Data Science, Bengaluru, India; Rajesh Kanna R., Christ University Computer Science, Bengaluru, India