A Large-Scale Secure Image Retrieval Method in Cloud Environment

Abstract

With the rapid development of cloud computing technology, more and more users choose to outsource image data to clouds. To protect data's confidentiality, images need to be encrypted before being outsourced to clouds, but this brings difficulties to some basic yet important data services, such as content-based image retrieval. Existing secure image retrieval methods generally have some problems such as low retrieval accuracy and low retrieval efficiency, which cannot meet requirements for large-scale image retrieval in cloud environment. In this paper, we propose a large-scale secure image retrieval method in cloud environment. The Hamming embedding algorithm is utilized to generate binary signatures of image descriptors. A frequency histogram combined with binary signatures is generated to provide a more precise representation of image features in an image and thus the retrieval accuracy is improved. Visual words are selected from the histogram by the random sampling method before the min-Hash algorithm is performed on binary signatures of selected visual words to generate a secure index. The random sampling method and min-Hash algorithm can not only ensure the security of the search index, but also greatly improve the image retrieval efficiency. This method achieves the balance among security, accuracy and efficiency of large-scale secure image retrieval in public clouds. The security analysis and experimental results show the effectiveness of the proposed method.