Dynamic Consensus Committee-Based for Secure Data Sharing With Authorized Multi-Receiver Searchable Encryption

计算机科学 加密 计算机安全 密文 钥匙(锁) 云计算 语义安全 公钥密码术 计算机网络 架空(工程) 随机预言 密钥管理 基于属性的加密 明文 数据共享 云存储 病理 操作系统 替代医学 医学
作者
Ningbin Yang,Chunming Tang,Qingsong Zhou,Debiao He
出处
期刊:IEEE Transactions on Information Forensics and Security [Institute of Electrical and Electronics Engineers]
卷期号:18: 5186-5199 被引量:2
标识
DOI:10.1109/tifs.2023.3305183
摘要

Data management services provided by the public cloud can economize the enterprise’s local storage costs, and meanwhile, realize data sharing among the enterprise. Corporate users, however, usually have concerns about the security and privacy of their data stored in the public cloud. Searchable encryption has been used as a secure method for enterprise users in the public cloud to share data via keyword search for many years. Nevertheless, conventional search and encryption primitives are challenging to realize several critical functions flexibly, such as key update, user revocation, lightweight computation, and low communication overhead for users, which will impede their widespread application. Besides, it may cause single-key-exposure security concerns by using untrusted devices. To address these issues, we present a dynamic consensus committee-based for secure data sharing with authorized multi-receiver searchable encryption (called DCC-SE), which exploits the blockchain dynamic committee to eliminate a single-key-exposure problem and enables fast keyword search without pairing and dynamic user management. The proposed DCC-SE scheme enjoys minor computation and communication overheads. It maintains a constant ciphertext size as the receiver increases. Furthermore, it periodically supports secure key and ciphertext updating and has been proven secure against chosen plaintext attacks and the chosen keyword guessing attacks under the random oracle model. The performance evaluation results show that DCC-SE has more feasibility and higher efficiency than the previous public key with keyword search(PEKS) schemes through theoretical analysis and simulation studies.
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