On Privacy Preserving Partial Image Sharing

摘要

Sharing photos through Online Social Networks becomes an increasingly popular fashion. However, users' privacy may be at stake when sensitive photos are shared improperly. This paper presents a dynamic privacy protection technique (named PuPPIeS) for image data where the data owner stipulates small private regions for sensitive objects (faces, SSN numbers, etc.) of a photo/image and sets different sharing policies for these partial regions with respect to different individuals. PuPPIeS is based on optimized reversible matrix perturbation of compressed image data. Hence it can naturally support frequently used image transformations. Our experiments show that our solution is effective for privacy protection and incurs only a small overhead for partial image sharing.