Jie Song (Institute of Information Engineering, Chinese Academy of Sciences; Intelligent Policing Key Laboratory of Sichuan Province, Sichuan Police College; School of Cyber Security, University of Chinese Academy of Sciences), Zhen Xu (Institute of Information Engineering, Chinese Academy of Sciences), Yan Zhang (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences), Pengwei Zhan (Sangfor Technologies Inc.), Mingxuan Li (School of Criminal Investigation, People's Public Security University of China), Shuai Ma (SKLCCSE Lab, Beihang University), Ru Xie (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences)
Keyword Private Information Retrieval (Keyword PIR) enables users to retrieve data associated with specific keywords from a database while keeping their queries private. However, existing Keyword PIR schemes struggle to support the boolean retrieval model, which is essential for practical applications that require logical combinations of terms.
This paper proposes a novel keyword PIR scheme leveraging advancements in homomorphic equality operations. It enables privacy-preserving retrieval over databases with many-to-many keyword-value mappings while supporting boolean operators for expressive search logic. Importantly, this extension preserves the core security guarantees of classical PIR. To the best of our knowledge, this is the first work to integrate keyword PIR with the boolean retrieval model.
Experimental evaluation shows that our scheme achieves a communication cost reduction proportional to the total number of values in the many-to-many keyword-value database, along with aggregate query processing performance gains that scale linearly with the number of values. These improvements enhance its feasibility for real-world applications such as privacy-preserving web search and patent retrieval.