Overview of Privacy-Enhancing Face Biometrics
— Prof. Peter Peer University of Ljubljana, Faculty of Computer and Information Science, Slovenia
Abstract
Biometric recognition technology has made significant advances over the last decade and is now used across a number of services and applications. However, this widespread deployment has also resulted in privacy concerns and evolving societal expectations about the appropriate use of the technology. For example, the ability to automatically extract age, gender, ... race, and health cues from biometric data has heightened concerns about privacy leakage.
Face recognition technology, in particular, has been in the spotlight, and is now seen by many as posing a considerable risk to personal privacy. In response to these and similar concerns, researchers have intensified efforts towards developing techniques and computational models capable of ensuring privacy to individuals, while still facilitating the utility of face recognition technology in several application scenarios. These efforts have resulted in a multitude of privacy--enhancing techniques that aim at addressing privacy risks originating from biometric systems and providing technological solutions for legislative requirements set forth in privacy laws and regulations, such as GDPR. The goal of this overview is to provide a comprehensive introduction into privacy--related research in the area of biometrics and review existing work on \textit{Biometric Privacy--Enhancing Techniques} (B--PETs) applied to face biometrics.
To make this work useful for as wide of an audience as possible, several key topics are covered as well, including evaluation strategies used with B--PETs, existing datasets, relevant standards, and regulations and critical open issues that will have to be addressed in the future.
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Biography
Peter Peer is a Full Professor at the Faculty of Computer and Information Science, University of Ljubljana, Slovenia, where he heads the Computer Vision Laboratory, coordinates the double degree study program with the Kyungpook National University, South Korea, and serves as a vice-dean for economic affairs.
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He received his PhD degree in computer science from the same institution in 2003. Within his post-doctorate he was an invited researcher at CEIT, Donostia – San Sebastian, Spain. He teaches courses on Operating systems, Game technology and virtual reality, and Image-based biometry. At the moment he is also a guest professor at the North-Caucasus Federal University, Russia.
His research interests include biometrics and computer vision. He participated in several national and EU funded R&D projects and published more than 100 research papers in leading international peer reviewed journals and conferences. He is a co-organizer of the Unconstrained Ear Recognition Challenge (2017, 2019) and Sclera Segmentation Benchmarking Competition (2020). He serves as an Associated Editor of IEEE Access and IET Biometrics. He is a member of the EAB, IAPR and IEEE, where he also served as a chairman of the Slovenian IEEE Computer chapter for four years.
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