10 citations · 12 across the 5 of their papers we have counts for
5 papers
MultiGait: A Multi-Sensor Multi-Perspective Multi-Session Biometric Inference Benchmark and its Dataset
Julian Todt, Felix Morsbach, Philip Dissert +1
A lack of suitable datasets has limited the research into the privacy risks of novel smart city sensors, such as thermal cameras, depth cameras, and lidar. Given the number of unsu…
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…
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…
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…
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…