Speaker: Raymond Veldhuis

The biometric comparator is the core engine of most biometric recognition systems. Its current realisations are predominantly based on machine learning. In the talk the underlying principles, which differ from those of standard machine-learning based classification, and their relation to statistical optimality will be reviewed. Afterwards, various security and privacy risks of the storage and processing of biometric data will be addressed and proposed privacy enhancing solutions discussed.

The event belongs to the Topical Program (TP) Algorithmization and Social Interaction, which is part of the TP Initiative of the University of Münster and was initiated by a consortium of researchers from the Faculty of Law, School of Business and Economics, and Faculty of Educational and Social Science at University of Münster. The project is lead by Prof. Dr. Heike Trautmann (SBE, Department of Information Systems).

The event is open to the public and will be streamed via Zoom.

For more information, please visit: www.algorithmization.org