A Model for Privacy-Preservation of User Query in Location-Based Services

Location-based services (LBS) can be a valuable tool for users seeking to find Points of Interest (POIs), but concerns about location privacy have become more prevalent in recent years. This research developed a privacy-preserving spatial keyword search method that enables users to look for POIs based on keywords without disclosing their location or the terms they are looking for in order to address this issue. Our approach utilises Privacy-Preserving Indexing (LPPI), which encrypts search queries and the POI database using quad-tree-based indexing to enable efficient and accurate searches. The LPPI system includes trapdoor generation, which encrypts search queries into a trapdoor that can be used to search the encrypted POI database, and secure search algorithms that enable the server to perform keyword searches on the encrypted database without revealing any information about the search queries or the POIs. This paper improves the LPPI technique by exploring ways to enhance the security and efficiency of trapdoor generation and search algorithms. The goal is to design a more robust and effective privacy-preserving spatial keyword search technique using web applications for a variety of LBS applications while protecting user privacy and respecting the rights of data owners.