A Privacy-Preserving Image Retrieval Based on AC-Coefficients and Color Histograms in Cloud Environment

Abstract

Content based image retrieval (CBIR) techniques have been widely deployed in many applications for seeking the abundant information existed in images. Due to large amounts of storage and computational requirements of CBIR, outsourcing image search work to the cloud provider becomes a very attractive option for many owners with small devices. However, owing to the private content contained in images, directly outsourcing retrieval work to the cloud provider apparently bring about privacy problem, so the images should be protected carefully before outsourcing. This paper presents a secure retrieval scheme for encrypted images in the YUV color space. First, the discrete cosine transform (DCT) is performed on Y component. The resulting DC coefficients are encrypted with stream cipher technology and AC coefficients are encrypted by using value permutation and position scrambling. In addition, U and V components are encrypted using the same encryption method as the AC coefficients. After that, the image owner transmits the encrypted images to the server. Second, the server extracts AC-coefficients histogram from encrypted Y component and two color histograms from encrypted U and V components, and combines these three histograms as image feature. After receiving a query trapdoor from one query user, the cloud server extracts query feature and computes Manhattan distance between query feature and database image feature. Finally, the encrypted images most similar to the query image are returned to the query user.