R&D: Encrypted De-Dupe Scheme Based on Files Diversity

The Journal of Supercomputing has published an article written by Xinfeng He, and Yifan Zhu, School of Cyber Security and Computer, Hebei University, Baoding, 071002, People’s Republic of China, and Key Lab on High Trusted Information System of Hebei Province, Baoding, 071002, People’s Republic of China.

Abstract: “In order to improve the efficiency of cloud storage, deduplication technology has been widely used. In personal cloud storage, files are diverse. Diverse files contain files of different sizes and different popularity, some of which have many copies. Existing deduplication schemes mainly focus on data security but fail to improve the overall performance, including low computing overhead for diverse data. Using deterministic tags based on convergent encryption to identify data may leak data information, while using fully random tags generated by complex encryption algorithms may generate more computing overhead. To address the above issues, we proposed an encrypted deduplication scheme based on files diversity (FD-Dedup). Diverse files are identified by semi-random tags. We also designed a semi-random tag generation (SRTG) algorithm that coordinates the computing overhead and security. Security analysis and performance comparison show that FD-Dedup can balance security and computing overhead for diverse files in personal cloud storage.“