PIC: Enable Large-Scale Privacy Preserving Content-Based Image Search on Cloud

Abstract

Many cloud platforms emerge to meet urgent requirements for large-volume personal image store, sharing and search. Though most would agree that images contain rich sensitive information (e.g., People, location and event) and people's privacy concerns hinder their participation into untrusted services, today's cloud platforms provide little support for image privacy protection. Facing large-scale images from multiple users, it is extremely challenging for the cloud to maintain the index structure and schedule parallel computation without learning anything about the image content and indices. In this work, we introduce a novel system PIC: a Privacy-preserving Image search system on Cloud, which is a step towards feasible cloud services which provide secure content-based large-scale image search with fine-grained access control. Users can search on others' images if they are authorized by the image owners. Majority of the computationally intensive jobs are handled by the cloud, and a querier can now simply send the query and receive the result. Specially, to deal with massive images, we design our system suitable for distributed and parallel computation and introduce several optimizations to further expedite the search process. Our security analysis and prototype system evaluation results show that PIC successfully protects the image privacy at a low cost of computation and communication.