Publication Type
Journal Article
Version
publishedVersion
Publication Date
1-2017
Abstract
Attribute-based encryption (ABE) has been widely used in cloud computing where a data provider outsources his/herencrypted data to a cloud service provider, and can share the data with users possessing specific credentials (or attributes). However,the standard ABE system does not support secure deduplication, which is crucial for eliminating duplicate copies of identical data inorder to save storage space and network bandwidth. In this paper, we present an attribute-based storage system with securededuplication in a hybrid cloud setting, where a private cloud is responsible for duplicate detection and a public cloud manages thestorage. Compared with the prior data deduplication systems, our system has two advantages. Firstly, it can be used to confidentiallyshare data with users by specifying access policies rather than sharing decryption keys. Secondly, it achieves the standard notion ofsemantic security for data confidentiality while existing systems only achieve it by defining a weaker security notion. In addition, we putforth a methodology to modify a ciphertext over one access policy into ciphertexts of the same plaintext but under other access policieswithout revealing the underlying plaintext.
Keywords
ABE, Storage, Deduplication
Discipline
Information Security | Software Engineering
Research Areas
Cybersecurity
Publication
IEEE Transactions on Big Data
Volume
PP
Issue
99
First Page
1
Last Page
13
Identifier
10.1109/TBDATA.2017.2656120
Publisher
Institute of Electrical and Electronics Engineers
Citation
CUI, Hui; DENG, Robert H.; LI, Yingjiu; and WU, Guowei.
Attribute-based storage supporting secure deduplication of encrypted data in cloud. (2017). IEEE Transactions on Big Data. PP, (99), 1-13.
Available at: https://ink.library.smu.edu.sg/sis_research/3898
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/TBDATA.2017.2656120