Lightweight attribute-based keyword search with policy protection for cloud-assisted IoT
Publication Type
Conference Proceeding Article
Publication Date
11-2019
Abstract
With the deep integration of the Internet of Things (IoT) and cloud computing, cloud-oriented IoT is embraced as an important paradigm for efficiency and productivity. On the other hand, it is also becoming an increasingly attractive target for cybercriminals, who attempt to breach data security and privacy. As a potential and promising solution to secure data, ciphertext-policy attribute-based keyword search (CP-ABKS) can provide both fine-grained keyword search and access control over the encrypted data. However, prior CP-ABKS schemes either fail to support lightweight computation or lack of policy protection. In this paper, with offline computation and inner product encryption, we propose a lightweight CP-ABKS scheme with policy protection, such that the encrypted data can be efficiently retrieved and accessed by data users in a fine-grained manner without leaking any sensitive information. We prove the correctness of the proposed scheme and its security in the standard model under the Decisional Bilinear Diffie-Hellman (DBDH) assumption. We also implement our proposed scheme to demonstrate its efficiency.
Keywords
attribute-based keyword search, Internet of Things, policy protection
Discipline
Information Security
Research Areas
Cybersecurity
Publication
2019 IEEE Conference on Dependable and Secure Computing 3rd DSC: Hangzhou, China, November 18-20: Proceedings
ISBN
9781728123196
Identifier
10.1109/DSC47296.2019.8937708
Publisher
IEEE
City or Country
Piscataway, NJ
Citation
SUN, Jianfei; XIONG, Hu; DENG, Robert H.; ZHANG, Yinghui; LIU, Ximeng; and CAO, Mingsheng.
Lightweight attribute-based keyword search with policy protection for cloud-assisted IoT. (2019). 2019 IEEE Conference on Dependable and Secure Computing 3rd DSC: Hangzhou, China, November 18-20: Proceedings.
Available at: https://ink.library.smu.edu.sg/sis_research/5071
Additional URL
https://doi.org/10.1109/DSC47296.2019.8937708