Multi-authority attribute-based keyword search over encrypted cloud data

• Main Authors: MIAO, Yibin, DENG, Robert H., LIU, Ximeng, CHOO, Kim-Kwang Raymond., WU, Hongjun, LI, Hongwei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: attribute-based encryption; multi-authority; Searchable encryption; selective-attribute model; selective-matrix model; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/5063; https://ink.library.smu.edu.sg/context/sis_research/article/6066/viewcontent/Multi_Authority_Attribute_Based_Keyword_Search_av.pdf
• Institution: Singapore Management University

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.