南京大学计算机科学与技术系

软件新技术与产业化协同创新中心

摘 要：

Encrypted deduplication seamlessly combines encryption and deduplication to simultaneously achieve both data confidentiality and storage efficiency. State-of-the-art encrypted deduplication systems mostly adopt a deterministic encryption approach that encrypts each plaintext chunk with a key derived from the content of the chunk itself, so that identical plaintext chunks are always encrypted into identical ciphertext chunks for deduplication. However, such deterministic encryption inherently reveals the underlying frequency distribution of the original plaintext chunks. This allows an adversary to launch frequency analysis against the resulting ciphertext chunks, and ultimately infer the content of the original plaintext chunks.

In this talk, we study how frequency analysis practically affects information leakage in encrypted deduplication storage, from both attack and defense perspectives. We propose a new inference attack that exploits chunk locality to increase the coverage of inferred chunks. Also, we present TED, a tunable encrypted deduplication primitive that provides a tunable mechanism for balancing the trade-off between storage efficiency and data confidentiality.

报告人简介：

Dr. Jingwei Li is an associate professor of University of Electronic Science and Technology of China. His research interest is to apply cryptographic technologies to build secure systems for large-scale data storage. His works have been published in top conference/journal venues, including USENIX ATC, Eurosys, ACM ToS, IEEE TDSC, IEEE TPDS, IEEE ToC, etc, and nominated for DSN 2017 best paper award.

时间:5月12日  14:00-15:00

地点:计算机科学技术楼225室