R&D: Practical Fuzzy De-Dupe for Encrypted Multimedia Data

The Journal of Industrial Information Integration has published an article written by Shuai Cheng, Zehui Tang, Shengke Zeng, School of Computer and Software Engineering, Xihua University, Chengdu 610000, PR China, Xinchun Cui, School of Foundational Education, University of Health and Rehabilitation Sciences, Qingdao 266000, PR China, and Tao Li, State Key Laboratory of Public Big Data, Guizhou University, Guiyang 550000, PR China.

Abstract: “Redundant data wastes cloud storage space, especially the multimedia data which comprises a large number of similar files and accounts for the majority of cloud storage. To protect privacy and eliminate redundancy in the cloud, fuzzy deduplication for encrypted multimedia data is practical and feasible. Unfortunately, existing fuzzy deduplications depend on aided server to be against security threats. In this paper, we propose a Practical Fuzzy Deduplication (PFDup) algorithm for encrypted multimedia data and it is secure against brute-force guessing attacks without additional independent severs. With our secure fuzzy deduplication technology, cloud storage can be significantly optimized by using Perceptual Hash (phash) to eliminate large quantities of identical even the similar multimedia data in a secure manner. In addition, PFDup protocol supports label consistency and a non-interactive Proof of Ownership (PO) in order to prevent the server–client collusion attacks. We conduct a series of experiments on numerous real-world datasets and the simulation results show that our deduplication rate for the similar images is over 91.5%.“