SEISA: Secure and efficient encrypted image search with access control

Abstract

Image search has been widely deployed in many applications for the rich content that images contain. In the era of big data, image search engines have to be hosted in data centers. As a viable solution, outsourcing the image search to public clouds is an economic choice for many small organizations. However, as many images contain sensitive information, e.g., healthcare information and personal faces/locations, directly outsourcing image search services to public clouds obviously raises privacy concerns. With this observation, several attempts are made towards secure image search over encrypted dataset, but they are limited by either search accuracy or search efficiency. In this paper, we propose a lightweight secure image search scheme over encrypted data, namely SEISA. Compared with image search techniques over plaintexts, SEISA only increases about 9% search cost and sacrifices about 3% on search accuracy. SEISA also efficiently supports search access control by employing a novel polynomial based design, which enables data owners to define who can search a specific image. Furthermore, we design a secure k-means outsourcing algorithm that significantly saves the data owner's cost. To demonstrate SEISA's performance, we implement a prototype of SEISA on Amazon EC2 cloud over a dataset with 10 million images.