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A Comprehensive Survey for Privacy-Preserving Biometrics: Recent Approaches, Challenges, and Future Directions

Shahriar Md Arman¹, Tao Yang^1,*, Shahadat Shahed², Alanoud Al Mazroa³, Afraa Attiah⁴, Linda Mohaisen⁴

1 School of Computer Science and Technology, Zhejiang Gongshang University, Hangzhou, 310018, China
2 School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, 310018, China
3 College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 84428, Saudi Arabia
4 Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

* Corresponding Author: Tao Yang. Email:

(This article belongs to the Special Issue: Multimedia Encryption and Information Security)

Computers, Materials & Continua 2024, 78(2), 2087-2110. https://doi.org/10.32604/cmc.2024.047870

Received 20 November 2023; Accepted 26 December 2023; Issue published 27 February 2024

Abstract

The rapid growth of smart technologies and services has intensified the challenges surrounding identity authentication techniques. Biometric credentials are increasingly being used for verification due to their advantages over traditional methods, making it crucial to safeguard the privacy of people’s biometric data in various scenarios. This paper offers an in-depth exploration for privacy-preserving techniques and potential threats to biometric systems. It proposes a noble and thorough taxonomy survey for privacy-preserving techniques, as well as a systematic framework for categorizing the field’s existing literature. We review the state-of-the-art methods and address their advantages and limitations in the context of various biometric modalities, such as face, fingerprint, and eye detection. The survey encompasses various categories of privacy-preserving mechanisms and examines the trade-offs between security, privacy, and recognition performance, as well as the issues and future research directions. It aims to provide researchers, professionals, and decision-makers with a thorough understanding of the existing privacy-preserving solutions in biometric recognition systems and serves as the foundation of the development of more secure and privacy-preserving biometric technologies.

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Keywords

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