Lightweight attribute-based keyword search with policy protection for cloud-assisted IoT

• Main Authors: SUN, Jianfei, XIONG, Hu, DENG, Robert H., ZHANG, Yinghui, LIU, Ximeng, CAO, Mingsheng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: attribute-based keyword search; Internet of Things; policy protection; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/5071
• Institution: Singapore Management University

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.