关键词: 云计算, 密文图像检索, 目标检测, 多重线性映射, 安全索引

Abstract:

More and more enterprise and individual users choose to store a large number of image files in the cloud server, and provide image retrieval and sharing functions. In order to protect the information of the stored important images from being stolen, image files are stored in the cloud server in encrypted form, which brings challenges to the image retrieval operation. The traditional plaintext retrieval schemes are no longer applicable, and how to guarantee the retrieval efficiency and accuracy of a large number of ciphertext images is also an important issue. According to the above problems, a ciphertext image retrieval scheme based on target detection in cloud environment is proposed. In the scheme, a target detection model named Faster R-CNN which is based on deep learning is used to extract keyword sets and feature vectors from images accurately, then the image sets are classified coarsely using the keyword sets, and the keywords are encrypted to construct secure indexes using the multiple linear mapping, so as to retrieve the matching image sets efficiently, at last the feature vectors of images are matched precisely to achieve the fine classification of images, retrieving the final images. The security analysis and performance evaluation show that the scheme has high security, retrieval efficiency and accuracy.

Key words: cloud computing, ciphertext image retrieval, object detection, multiple linear mapping, security index