DYSAN: Dynamically sanitizing motion sensor data against sensitive inferences through adversarial networks

1 code implementation • 23 Mar 2020 • Claude Rosin Ngueveu, Antoine Boutet, Carole Frindel, Sébastien Gambs, Théo Jourdan, Claude Rosin

However, nothing prevents the service provider to infer private and sensitive information about a user such as health or demographic attributes. In this paper, we present DySan, a privacy-preserving framework to sanitize motion sensor data against unwanted sensitive inferences (i. e., improving privacy) while limiting the loss of accuracy on the physical activity monitoring (i. e., maintaining data utility).

Activity Recognition Attribute +2