A secure retrieval method for large-scale images in cloud environment

Abstract

The invention belongs to the field of multimedia information security protection, in particular to an image security retrieval method based on the combination of a word bag model and a minimum hash principle, which can be used for the security retrieval of large-scale images. A content owner combines a sack model with the minimum hash principle to construct a secure index of the image features. Inthe safe index data set of image features, the noise index vector is introduced, and the index vector corresponding to some visual words is randomly extracted to construct the safe index table. The image security index table and the encrypted image are uploaded to the cloud server. When the user requests retrieval, the cloud service only searches the index table according to the query image indexinformation, and the user obtains the image to be retrieved according to the similarity between the index vectors. This retrieval method has higher efficiency and is more suitable for large-scale dataset retrieval. The feature vector based on SIFT descriptor and binary signature can achieve high precision matching, and has high retrieval accuracy.

Description

technical field [0001] The invention belongs to the field of multimedia information security protection, and in particular relates to an image security retrieval method based on a bag-of-words model combined with a minimum hash principle, which can be used for security retrieval of large-scale images. Background technique [0002] With the popularization of digital cameras and smart phones, people's access to data has become more and more convenient, and multimedia data such as images has shown an explosive growth trend. A cloud computing platform that integrates grid, parallel processing, and distributed processing provides a strong guarantee for massive data services and application processing with its low cost, powerful computing capabilities, and nearly unlimited resource pools. More and more of users choose to upload image data to a cloud server for storage and processing. However, data outsourced to the cloud is completely out of the direct physical control of its own...

AI Technical Summary

Problems solved by technology

The data owner generates a ciphertext image and an encrypted index and uploads it to the cloud. During the retrieval process, the cloud can return the ciphertext image closest to the query image without decryption, which can effectively solve the problem of existing solutions that cannot balance security, accuracy, and efficiency. The problem

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