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Paper 2022/1133

Secure Batch Deduplication Without Dual Servers in Backup System

Haoyu Zheng, Xihua University
Shengke Zeng, Xihua University
Hongwei Li, University of Electronic Science and Technology of China
Zhijun Li, Cisco
Abstract

Cloud storage provides highly available and low cost resources to users. However, as massive amounts of outsourced data grow rapidly, an effective data deduplication scheme is necessary. This is a hot and challenging field, in which there are quite a few researches. However, most of previous works require dual-server fashion to be against brute-force attacks and do not support batch checking. It is not practicable for the massive data stored in the cloud. In this paper, we present a secure batch deduplication scheme for backup system. Besides, our scheme resists the brute-force attacks without the aid of other servers. The core idea of the batch deduplication is to separate users into different groups by using short hashes. Within each group, we leverage group key agreement and symmetric encryption to achieve secure batch checking and semantically secure storage. We also extensively evaluate its performance and overhead based on different datasets. We show that our scheme saves the data storage by up to 89.84%. These results show that our scheme is efficient and scalable for cloud backup system and can also ensure data confidentiality.

Metadata
Available format(s)
PDF
Category
Applications
Publication info
Preprint.
Keywords
Cloud Storage Semantic Security Batch deduplication Brute-force Attack
Contact author(s)
Ricardozhy @ outlook com
zengshengke @ gmail com
hongweili @ uestc endu cn
ansli @ cisco com
History
2022-08-31: approved
2022-08-31: received
See all versions
Short URL
https://ia.cr/2022/1133
License
Creative Commons Attribution-ShareAlike
CC BY-SA

BibTeX

@misc{cryptoeprint:2022/1133,
      author = {Haoyu Zheng and Shengke Zeng and Hongwei Li and Zhijun Li},
      title = {Secure Batch Deduplication Without Dual Servers in Backup System},
      howpublished = {Cryptology {ePrint} Archive, Paper 2022/1133},
      year = {2022},
      url = {https://eprint.iacr.org/2022/1133}
}
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