Balancing Storage Efficiency and Data Confidentiality with Tunable Encrypted Deduplication.

Conventional encrypted deduplication approaches retain the deduplication capability on duplicate chunks after encryption by always deriving the key for encryption/decryption from the chunk content, but such a deterministic nature causes information leakage due to frequency analysis. We present TED, a tunable encrypted deduplication primitive that provides a tunable mechanism for balancing the tradeoff between storage efficiency and data confidentiality. The core idea of TED is that its key derivation is based on not only the chunk content but also the number of duplicate chunk copies, such that duplicate chunks are encrypted by distinct keys in a controlled manner. In particular, TED allows users to configure a storage blowup factor, under which the information leakage quantified by an information-theoretic measure is minimized for any input workload. We implement an encrypted deduplication prototype TEDStore to realize TED in networked environments. Evaluation on real-world file system snapshots shows that TED effectively balances the trade-off between storage efficiency and data confidentiality, with small performance overhead.