A dynamic authorizable ciphertext image retrieval algorithm based on security neural network inference.

ABSTRACT: In this paper, we propose a dynamic authorizable ciphertext image retrieval scheme based on secure neural network inference that effectively enhances the security of image retrieval while preserving privacy. To ensure the privacy of the original image and enable feature extraction without decryption operations, we employ a secure neural network for feature extraction during the index construction stage of encrypted images. Additionally, we introduce a dynamic authenticatable ciphertext retrieval algorithm to enhance system flexibility and security by enabling users to quickly and flexibly retrieve authorized images. Experimental results demonstrate that our scheme guarantees data image privacy throughout the entire process from upload to retrieval compared to similar literature schemes. Fu

SUBMITTER: Zhang XY 

PROVIDER: S-EPMC11498660 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature