Design of Privacy Protection System for Target Search Based on Selection Algorithm and Sustainable Iteration Index

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Wei Zheng, Tao Liu, Lihong Hao, Jiwei Tang

Abstract

The data self-destruct method based on privacy cloud proposed in this paper can realize the automatic destruction of cloud data after expiration, and based on this method, a self-destruct image protection system is implemented. This project intends to combine the adaptive scale invariant Feature conversion (SIFT) extraction of ciphertext images with binary SIFT to ensure the confidentiality of the images uploaded to the server in the ciphertext space. The security protection of data is realized using Paillier homomorphic encryption technology. The feature of SIFT is extracted from the encrypted region, and it is expressed in binary form to reduce the amount of computation and memory overhead. The experimental results show that this method can effectively prevent the automatic destruction of images after expiration, so as to ensure that the user's personal information is not leaked.

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