Enabling Efficient, Verifiable, and Secure Conjunctive Keyword Search in Hybrid-Storage Blockchains

• Published in: IEEE transactions on knowledge and data engineering Vol. 36; no. 6; pp. 2445 - 2460
• Main Authors: Cui, Ningning, Wang, Dong, Li, Jianxin, Zhu, Huaijie, Yang, Xiaochun, Xu, Jianliang, Cui, Jie, Zhong, Hong
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-06-2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Blockchain; Blockchains; conjunctive keyword search; Cryptography; Data privacy; Design optimization; dynamic updates; Empirical analysis; Indexes; Keyword search; Privacy; privacy-preserving; result verification; Security; Servers; Synthetic data; Verification
• ISSN: 1041-4347; 1558-2191
• DOI: 10.1109/TKDE.2023.3324128

Blockchain has emerged as a prevailing paradigm for decentralized applications due to its reliability and transparency. To scale up retrieval services, a common strategy is to use a hybrid storage model, where on-chain storage is responsible for small metadata and off-chain storage is for outsourced raw data. However, data security and result authenticity are ongoing challenges in this scenario, and little work has been done due to the difficulty of combining result verification and privacy preservation, especially for dynamic updates while supporting forward privacy. In this paper, we formally define the problem of efficient, verifiable, and secure conjunctive keyword search in hybrid-storage blockchains (vsChain) and propose a novel hybrid index that achieves efficient query and verification while supporting dynamic updates with forward privacy guarantee. We also design two optimized schemes to improve query and verification performance by using a partition-based method and an obfuscated counting Bloom filter mechanism. Finally, we provide a theoretical security analysis and empirical evaluations using real and synthetic datasets to demonstrate the feasibility of our proposed schemes.