Security-Aware and Efficient Data Deduplication for Edge-Assisted Cloud Storage Systems
Qingyuan Xie, Chen Zhang, Xiaohua Jia
Abstract
Data deduplication at the network edge significantly improves communication efficiency in edge-assisted cloud storage systems. With the increasing concern about data privacy, secure deduplication has been proposed to provide data security while supporting deduplication. Since conventional secure deduplication schemes are mainly based on deterministic encryption, they are vulnerable to frequency analysis attacks. Some recent research has focused on this problem, where several works studied the trade-off between deduplication efficiency and resistance to frequency analysis attacks. However, no existing work can provide different deduplication efficiency and protection for different data chunks. In this paper, we propose a security-aware and efficient data deduplication scheme for edge-assisted cloud storage systems. It not only improves the efficiency of deduplication but also reduces information leakage caused by frequency analysis attacks. In particular, we first define the security level for chunks to measure the security needs of users. Then, we develop an encryption scheme with multiple levels of security for deduplication. It provides higher security protection for chunks with higher security levels, while sacrificing security to achieve higher deduplication efficiency for chunks with lower security levels. We also analyze the security of our proposed scheme. Evaluations on the real-world datasets show the efficiency of our design.