FuzzyDedup: Secure Fuzzy Deduplication for Cloud Storage

Abstract

Data deduplication is of critical importance to reduce the storage cost for clients and to relieve the unnecessary storage pressure for cloud servers. While various techniques have been proposed for secure deduplication of identical files/blocks, the effective and secure deduplication solutions on fuzzy similar data (image, video, and others) which occupy a large portion in the real world across wide applications, remain open. In this paper, we propose a novel deduplication system, named Fuzzy Deduplication (FuzzyDedup), to implement the secure deduplication of similar data (i.e., similar files, chunks, or blocks). In particular, we leverage the similarity-preserving hash, a fuzzy extractor based on error-correcting codes, and the encryption with customized design to construct a fuzzy-style deduplication encryption scheme (FuzzyMLE), achieving the ciphertext-based deduplication for similar data. Besides, to defend against data ownership cheating attack and duplicate-faking attack, a fuzzy-style proof of ownership scheme (FuzzyPoW) is designed for the cloud server to securely verify a client in possession of the similar data. To further enhance security and efficiency, we also propose both server-aided and random-tag FuzzyMLE to make FuzzyDedup robust against off-line brute-force attack and to support tag randomization, respectively. Then, we design Hamming distance reduction and tag cutting optimization algorithms to improve the tag query efficiency of FuzzyDedup. In the end, we formally prove the security of our solution and conduct experiments on real-world datasets for performance evaluation. Experimental results exhibit the efficiency of FuzzyDedup in terms of computation cost and communication overhead.