Publication Type
Journal Article
Version
acceptedVersion
Publication Date
8-2019
Abstract
Internet of Things (IoT) cloud provides a practical and scalable solution to accommodate the data management in large-scale IoT systems by migrating the data storage and management tasks to cloud service providers (CSPs). However, there also exist many data security and privacy issues that must be well addressed in order to allow the wide adoption of the approach. To protect data confidentiality, attribute-based cryptosystems have been proposed to provide fine-grained access control over encrypted data in loT cloud. Unfortunately, the existing attributed-based solutions are still insufficient in addressing some challenging security problems, especially when dealing with compromised or leaked user secret keys due to different reasons. In this paper, we present a practical attribute-based access control system for loT cloud by introducing an efficient revocable attribute-based encryption scheme that permits the data owner to efficiently manage the credentials of data users. Our proposed system can efficiently deal with both secret key revocation for corrupted users and accidental decryption key exposure for honest users. We analyze the security of our scheme with formal proofs, and demonstrate the high performance of the proposed system via experiments. (C) 2019 Elsevier B.V. All rights reserved.
Keywords
IoT cloud, Attribute-based encryption, Revocation, Decryption key exposure
Discipline
Information Security
Research Areas
Cybersecurity
Publication
Future Generation Computer Systems
Volume
97
First Page
284
Last Page
294
ISSN
0167-739X
Identifier
10.1016/j.future.2019.02.051
Publisher
Elsevier
Citation
XU, Shengmin; YANG, Guomin; MU, Yi; and LIU, Ximeng.
A secure IoT cloud storage system with fine-grained access control and decryption key exposure resistance. (2019). Future Generation Computer Systems. 97, 284-294.
Available at: https://ink.library.smu.edu.sg/sis_research/5150
Copyright Owner and License
Authors
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/10.1016/j.future.2019.02.051