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cs.CR2025

FacialMotionID: Identifying Users of Mixed Reality Headsets using Abstract Facial Motion Representations

Adriano Castro, Simon Hanisch, Matin Fallahi +1

Facial motion capture in mixed reality headsets enables real-time avatar animation, allowing users to convey non-verbal cues during virtual interactions. However, as facial motion…

cs.CR2025

Pantomime: Motion Data Anonymization using Foundation Motion Models

Simon Hanisch, Julian Todt, Thorsten Strufe

Human motion is a behavioral biometric trait that can be used to identify individuals and infer private attributes such as medical conditions. This poses a serious threat to privac…

cs.CR2024

SEBA: Strong Evaluation of Biometric Anonymizations

Julian Todt, Simon Hanisch, Thorsten Strufe

Biometric data is pervasively captured and analyzed. Using modern machine learning approaches, identity and attribute inferences attacks have proven high accuracy. Anonymizations a…

cs.CR2024

A False Sense of Privacy: Towards a Reliable Evaluation Methodology for the Anonymization of Biometric Data

Simon Hanisch, Julian Todt, Jose Patino +2

Biometric data contains distinctive human traits such as facial features or gait patterns. The use of biometric data permits an individuation so exact that the data is utilized eff…

cs.CR2024

Fantômas: Understanding Face Anonymization Reversibility

Julian Todt, Simon Hanisch, Thorsten Strufe

Face images are a rich source of information that can be used to identify individuals and infer private information about them. To mitigate this privacy risk, anonymizations employ…