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A secure privacy preserving deduplication scheme for cloud computing

delete2019-12-01
delete27
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OA
AI
Y
Yongkai Fan
Xiaodong Lin 封面图
Xiaodong Lin (Xiaodong Lin)
韦
韦良 (Wei Liang) *
G
Gang Tan
P
Priyadarsi Nanda
DOI:10.1016/j.future.2019.04.046delete
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摘要

摘要

En 中文
Data deduplication is a key technique to improve storage efficiency in cloud computing. By pointing redundant files to a single copy, cloud service providers greatly reduce their storage space as well as data transfer costs. Despite of the fact that the traditional deduplication approach has been adopted widely, it comes with a high risk of losing data confidentiality because of the data storage models in cloud computing. To deal with this issue in cloud storage, we first propose a TEE (trusted execution environment) based secure deduplication scheme. In our scheme, each cloud user is assigned a privilege set; the deduplication can be performed if and only if the cloud users have the correct privilege. Moreover, our scheme augments the convergent encryption with users' privileges and relies on TEE to provide secure key management, which improves the ability of such cryptosystem to resist chosen plaintext attacks and chosen ciphertext attacks. A security analysis indicates that our scheme is secure enough to support data deduplication and to protect the confidentiality of sensitive data. Furthermore, we implement a prototype of our scheme and evaluate the performance of our prototype, experiments show that the overhead of our scheme is practical in realistic environments. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
Deduplication
Trusted execution environment
Cloud storage
Encryption
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期刊

F
Future Generation Computer Systems-The International Journal of eScience
IF:
6.1
论文数:
6.8K
被引数:
2.3W

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Chifeng University
学者数:
499
论文数: 350
被引数: 394
P
Pennsylvania State University
学者数:
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论文数: 2.6W
被引数: 7.2W
P
pennsylvania commonwealth system of higher education (pcshe)
学者数:
12.9W
论文数: 11.7W
被引数: 177
H
hunan university
学者数:
4.5W
论文数: 3.3W
被引数: 70
C
china university of petroleum
学者数:
4.1W
论文数: 2.7W
被引数: 30
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