Efficient Private Information Retrieval Scheme with Dynamic Database

Private information retrieval (PIR) is a typical application scenario of encrypted computing, which allows users to retrieve data from a database by providing only an encrypted index. In an academic research scenario, multiple parties may entrust their data to a third party and require collaborative retrieval. However, due to competitive relationships and mutual distrust between these parties, they do not share public–private keys, making single-key mechanisms inadequate for meeting actual privacy requirements. In this case, based on the multi-key fully homomorphic encryption (MKFHE) algorithm, we construct an efficient PIR scheme with an access permission verification mechanism and dynamic database. Specifically, we design an MKFHE algorithm to protect multi-user privacy information. The vector–matrix multiplication optimization algorithm is adopted to improve computational efficiency, the expand algorithm is used to reduce user communication traffic, and homomorphic multiplication with ciphertext chunking is used to avoid excessive noise caused by direct ciphertext multiplication. Experiments based on the SEAL library show that by transferring part of the computational pressure to the offline stage, the online query response efficiency of our scheme is improved by about 7.69%, and the online computational efficiency of vector–matrix multiplication is improved by about 19.7%.