Multi-authority Attribute-Based Keyword Search over encrypted cloud data

Searchable Encryption (SE) is an important technique to guarantee data security and usability in the cloud at the same time. Leveraging Ciphertext-Policy Attribute-Based Encryption (CP-ABE), the Ciphertext-Policy Attribute-Based Keyword Search (CP-ABKS) scheme can achieve keyword-based retrieval and...

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Main Authors: Miao, Yinbin, Deng, Robert H., Liu, Ximeng, Choo, Kim-Kwang Raymond, Wu, Hongjun, Li, Hongwei
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/160299
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1602992022-07-19T02:29:14Z Multi-authority Attribute-Based Keyword Search over encrypted cloud data Miao, Yinbin Deng, Robert H. Liu, Ximeng Choo, Kim-Kwang Raymond Wu, Hongjun Li, Hongwei School of Physical and Mathematical Sciences Engineering::Computer science and engineering Cloud Computing Encryption Searchable Encryption (SE) is an important technique to guarantee data security and usability in the cloud at the same time. Leveraging Ciphertext-Policy Attribute-Based Encryption (CP-ABE), the Ciphertext-Policy Attribute-Based Keyword Search (CP-ABKS) scheme can achieve keyword-based retrieval and fine-grained access control simultaneously. However, the single attribute authority in existing CP-ABKS schemes is tasked with costly user certificate verification and secret key distribution. In addition, this results in a single-point performance bottleneck in distributed cloud systems. Thus, in this paper, we present a secure Multi-authority CP-ABKS (MABKS) system to address such limitations and minimize the computation and storage burden on resource-limited devices in cloud systems. In addition, the MABKS system is extended to support malicious attribute authority tracing and attribute update. Our rigorous security analysis shows that the MABKS system is selectively secure in both selective-matrix and selective-attribute models. Our experimental results using real-world datasets demonstrate the efficiency and utility of the MABKS system in practical applications. 2022-07-19T02:29:14Z 2022-07-19T02:29:14Z 2019 Journal Article Miao, Y., Deng, R. H., Liu, X., Choo, K. R., Wu, H. & Li, H. (2019). Multi-authority Attribute-Based Keyword Search over encrypted cloud data. IEEE Transactions On Dependable and Secure Computing, 18(4), 1667-1680. https://dx.doi.org/10.1109/TDSC.2019.2935044 1545-5971 https://hdl.handle.net/10356/160299 10.1109/TDSC.2019.2935044 2-s2.0-85070968213 4 18 1667 1680 en IEEE Transactions on Dependable and Secure Computing © 2019 IEEE. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Cloud Computing
Encryption
spellingShingle Engineering::Computer science and engineering
Cloud Computing
Encryption
Miao, Yinbin
Deng, Robert H.
Liu, Ximeng
Choo, Kim-Kwang Raymond
Wu, Hongjun
Li, Hongwei
Multi-authority Attribute-Based Keyword Search over encrypted cloud data
description Searchable Encryption (SE) is an important technique to guarantee data security and usability in the cloud at the same time. Leveraging Ciphertext-Policy Attribute-Based Encryption (CP-ABE), the Ciphertext-Policy Attribute-Based Keyword Search (CP-ABKS) scheme can achieve keyword-based retrieval and fine-grained access control simultaneously. However, the single attribute authority in existing CP-ABKS schemes is tasked with costly user certificate verification and secret key distribution. In addition, this results in a single-point performance bottleneck in distributed cloud systems. Thus, in this paper, we present a secure Multi-authority CP-ABKS (MABKS) system to address such limitations and minimize the computation and storage burden on resource-limited devices in cloud systems. In addition, the MABKS system is extended to support malicious attribute authority tracing and attribute update. Our rigorous security analysis shows that the MABKS system is selectively secure in both selective-matrix and selective-attribute models. Our experimental results using real-world datasets demonstrate the efficiency and utility of the MABKS system in practical applications.
author2 School of Physical and Mathematical Sciences
author_facet School of Physical and Mathematical Sciences
Miao, Yinbin
Deng, Robert H.
Liu, Ximeng
Choo, Kim-Kwang Raymond
Wu, Hongjun
Li, Hongwei
format Article
author Miao, Yinbin
Deng, Robert H.
Liu, Ximeng
Choo, Kim-Kwang Raymond
Wu, Hongjun
Li, Hongwei
author_sort Miao, Yinbin
title Multi-authority Attribute-Based Keyword Search over encrypted cloud data
title_short Multi-authority Attribute-Based Keyword Search over encrypted cloud data
title_full Multi-authority Attribute-Based Keyword Search over encrypted cloud data
title_fullStr Multi-authority Attribute-Based Keyword Search over encrypted cloud data
title_full_unstemmed Multi-authority Attribute-Based Keyword Search over encrypted cloud data
title_sort multi-authority attribute-based keyword search over encrypted cloud data
publishDate 2022
url https://hdl.handle.net/10356/160299
_version_ 1739837388837879808