Enhancing Searchable Symmetric Encryption Performance through Optimal Locality

Both individuals and institutions place great importance on maintaining the security and privacy of their data, when stored in the cloud server. To achieve this, they often turn to searchable symmetric encryption (SSE), which is considered a crucial technology for safeguarding user data. However, SSE has encountered some challenges, particularly in the case of large databases. One such issue is poor performance, which can be attributed to poor locality. This means that the cloud server must visit a large number of locations during the search process, resulting in slow retrieval times. The main problem however, is not just poor locality. In many cases, optimization methods intended to improve performance can actually lead to increased storage requirements for the encrypted index stored on the cloud server or reduced efficiency when reading data. These issues must be addressed in order for SSE to continue to be an effective tool for protecting sensitive information. In this paper, we introduce a secure and searchable scheme that effectively addresses the issues mentioned above, while also enhancing the performance of information retrieval through an improved encrypted inverted index storage mechanism. Our scheme achieves optimal locality at , and read efficiency at , thereby significantly increasing the speed of retrieval. Through experimentation with real-world data, we have demonstrated the practicality, accuracy, and security of our approach, making it a reliable solution for secure and efficient information retrieval.