Practical Multisource–Multiclient Conjunctive Searchable Encryption With Forward and Backward Privacy for Cloud–IoT
Sensen Li, Yicai Huang, Zhengxin Fu, Bin Yu · IEEE Internet of Things Journal · 2025
Searchable encryption has garnered considerable attention for its ability to empower users to perform searches on encrypted data stored remotely without compromising confiden-tiality. Multi-source multi-client (M/M) searchable symmetric encryption excels in efficiently outsourcing and sharing data from multiple data sources, making it ideal for cloud-IoT applications with numerous terminal devices. However, empirical analysis shows that the recently proposed M/M scheme, despite being potentially the most representative scheme currently available, still confronts two primary challenges. First, it only supports single keyword searches, which constrains its applicability in more complex query scenarios. Second, it focuses exclusively on forward privacy but neglects backward privacy, potentially leaving sensitive information vulnerable during dynamic data updates. To tackle these issues, we propose a new multi-source multi-client conjunctive searchable encryption (MMCSE) scheme, which enables non-interactive conjunctive searches while ensur-ing both forward and backward privacy. Building on this foun-dation, we further bolster security and functionality with the enhanced scheme named eMMCSE. By leveraging puncturable pseudorandom functions and n-dimensional dynamic symmetric hidden vector encryption (n-DSHVE), eMMCSE effectively minimizes result pattern leakage and provides the revocation mechanism, supporting both coarse-grained revocation of specific clients and fine-grained revocation of particular records. The security analysis demonstrates that the proposed schemes are secure against the adversarial server and colluding clients. Addi-tionally, experimental results highlight their marked enhance-ments in search efficiency across most scenarios.