摘要 : Data deduplication has been widely used in the cloud to reduce storage space. To protect data security, users encrypt data with message-locked encryption (MLE) to enable deduplication over ciphertexts. However, existing secure ded... 展开 Data deduplication has been widely used in the cloud to reduce storage space. To protect data security, users encrypt data with message-locked encryption (MLE) to enable deduplication over ciphertexts. However, existing secure deduplication schemes suffer from security weakness (i.e., brute-force attacks) and fail to support flexible access control. The process of chunk-level MLE key generation and sharing exists potential privacy issues and heavy computation consumption.We propose EDedup, a similarity-aware encrypted deduplication scheme that supports flexible access control with revocation. Specifically, EDedup groups files into segments and performs server-aided MLE at segment-level, which exploits similarity via a representative hash (e.g., the min-hash) to reduce computation consumption. This nevertheless faces a new attack that an attacker gets keys by guessing the representative hash. And hence EDedup combines source-based similar-segment detection and target-based duplicate-chunk checking to resist attacks and guarantee deduplication efficiency. Furthermore, EDedup generates message-derived file keys for duplicate files to manage metadata. EDedup encrypts file keys via proxy-based attribute-based encryption, which reduces metadata storage overheads and implements flexible access control with revocation. Evaluation results demonstrate that EDedup improves the speed of MLE up to 10.9X and 0.36X compared with DupLESS-chunk and SecDep respectively. EDedup reduces metadata storage overheads by 39.9%–65.7% relative to REED. 收起