Secure fuzzy retrieval protocol for multiple datasets

With the diversification of data sources and the massive growth of datasets, data retrieval has become increasingly complex and time-consuming. In the traditional retrieval method, if a user wants to query multiple datasets, the general approach is to retrieve them one by one in order, which may lead to duplication of work and waste of resources. Private set intersection is a specific issue insecure multi-party computation. It allows several participants, each holding different sets, to jointly calculate the intersection of their sets without revealing any information other than the intersection. This method is naturally suitable for data fusion. In this work, we propose a secure fuzzy retrieval protocol for multiple datasets. First, we use private set intersection technology to fuse multiple datasets. Then, we perform secure retrieval based on this fused dataset, effectively avoiding the waste of resources caused by separate retrievals, thereby maximizing resource efficiency. It is worth mentioning that the protocol proposed in this paper can also be used for fuzzy retrieval to improve the user's search experience. More importantly, the protocol can maximize privacy protection during the retrieval process, including strict protection of sensitive information such as retrieval keywords, ensuring that user data and query intentions will not be leaked during the entire retrieval process. Finally, we provide a rigorous security proof and demonstrate the effectiveness of the protocol through simulation experiments.