Security-Aware and Efficient Data Deduplication for Edge-Assisted Cloud Storage Systems

Qingyuan Xie*, Chen Zhang, Xiaohua Jia

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

14 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)2191-2202
Number of pages12
JournalIEEE Transactions on Services Computing
Volume16
Issue number3
Online published1 Aug 2022
DOIs
Publication statusPublished - May 2023

Funding

This work was supported by the Research Grants Council of Hong Kong under Grants CityU 11202419 and R1012-21.

Research Keywords

  • Cloud computing
  • Edge-assisted cloud storage systems
  • Encryption
  • frequency analysis
  • Maximum likelihood estimation
  • Resistance
  • Resists
  • Security
  • security-aware deduplication
  • Servers

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