Efficient Privacy Preserving Video Surveillance

Abstract

Widespread use of surveillance cameras in offices and other business establishments, pose a significant threat to the privacy of the employees and visitors. The challenge of introducing privacy and security in such a practical surveil- lance system has been stifled by the enormous computa- tional and communication overhead required by the solu- tions. In this paper, we propose an efficient framework to carry out privacy preserving surveillance. We split each frame into a set of random images. Each image by itself does not convey any meaningful information about the orig- inal frame, while collectively, they retain all the informa- tion. Our solution is derived from a secret sharing scheme based on the Chinese Remainder Theorem, suitably adapted to image data. Our method enables distributed secure pro- cessing and storage, while retaining the ability to recon- struct the original data in case of a legal requirement. The system installed in an office like environment can effectively detect and track people, or solve similar surveillance tasks. Our proposed paradigm is highly efficient compared to Se- cure Multiparty Computation, making privacy preserving surveillance, practical.