Explicitly Privacy-Aware Space Usage Analysis
Sanjiv S. Jha, Simon Mayer, Tanja Schneider · 2020
Surveillance in private and public spaces provides observers with information that can enhance protection and efficiency but usually infringes upon the privacy of the individuals and groups. These informational privacy risks are centered on users' perceived and design-induced threats. They cannot be removed completely but can be minimized using suitable anonymization techniques. To minimize the users' informational privacy threats, we designed a privacy-aware surveillance system that gives the users leverage over the anonymization filters, to physically adjust the opaqueness of the camera lens used in the prototype according to their privacy requirements. We implement our prototype in the context of office space surveillance, where the proposed solution considers privacy requirements in such environments to improve users' trust in the surveillance system and reduce their privacy concerns.