An AES-Based Secure Image Retrieval Scheme Using Random Mapping and BOW in Cloud Computing

Abstract

With the rapid growth of the number of images, many content-based image retrieval methods have been extensively used in our daily life. In general, image retrieval services are very expensive in terms of computing and storage. Therefore, outsourcing services to the cloud server is a good choice for image owners. However, privacy protection can become a big issue for image owners because the cloud server can only be semi-trusted. In this paper, we propose a novel image retrieval scheme. It is a ciphertext image retrieval method based on random mapping features with the bag-of-words model. After encrypting the image with Advanced Encryption Standard and block permutation, the cloud server generates random templates and then extracts the local features. All local features are clustered by k-means algorithm to form the visual word. The histogram of encrypted visual words is constructed in this way as the feature vector to represent each image. The similarity between images can be measured by the distance between feature vectors on the cloud server. Experiments and analysis prove the effect of the scheme. INDEX TERMS Image retrieval, AES encryption, BOW model, random mapping.

A Privacy-Preserving Image Retrieval Scheme Using A Codebook Generated From Independent Plain-Image Dataset

“…In addition, some secret information is shared between the image owner and users [4], [11]. In contrast, in the second approach, descriptors are directly extracted from encrypted images without decryption by cloud providers [5], [12]- [16], and the image owner has no secret information that should be shared with users. The proposed scheme corresponds to this approach.…”

“…The proposed scheme corresponds to this approach. Bag-of-visual words (BOVW) model-based [5], [12], [15]- [18] and JPEG-based [13], [14] schemes are also in this approach.…”

Privacy-Preserving Content-Based Image Retrieval Using Compressible Encrypted Images

“…In the second approach, descriptors are directly extracted from encrypted images by a cloud provider as well as for plain images [12]- [17], where each data owner only encrypts images. In addition, data owners and users do not need to share keys.…”

“…The proposed retrieval scheme corresponds to this approach. Schemes [12]- [17] are carried out the basis on this approach. Some schemes [15], [16] consider compressing images with JPEG, but their retrieval performance will be degraded due to the difference in coding parameters used for JPEG compression.…”

Color Image Retrieval Algorithm Fusing Color and Principal Curvatures Information

“…With the application of computer vision and digital devices, image processing is more and more widely used in medical images [1], [2], image super-resolution [3], [4], remote sensing images [5], and other fields such as social applications [6], [7]. Nowadays, benefiting from the rapid development of image processing, people can get access to image resources quickly.…”