Fuzzy Multi-Keyword Search for Multi-Owner Scenario in IoV

As the Internet of Vehicles (IoV) continues to evolve, data owners consistently upload private information to the nearest roadside unit (RSU), which may pose significant risks of privacy leakage. Searchable encryption (SE) technology stands as an effective method to mitigate this issue. However, during data retrieval via the on-board unit (OBU), users may encounter inaccurate search results stemming from spelling errors or similar keyword inputs. Consequently, the combination of SE with fuzzy keyword search has garnered increasing attention. Nevertheless, existing schemes often overlook the necessity for efficient access control, thereby exacerbating the risks of data leakage and unauthorized tampering within the IoV. Moreover, many of these solutions cater solely to single-owner models, limiting their applicability in IoV environments characterized by multiple data sources. Furthermore, fuzzy search schemes relying on locality-sensitive hashing (LSH) for index construction may inadvertently result in keyword insertion leakage. To address these challenges, we propose a fuzzy multi-keyword search scheme (FAMI) tailored for multi-owner IoV scenarios. Specifically, FAMI integrates a linear secret-sharing scheme (LSSS) with attribute-based keyword search, supporting a robust multi-to-multi model with effective access control. Additionally, an indistinguishable bloom filter (IBF) is utilized in conjunction with bi-gram keyword conversion technology to enhance the mapping accuracy for similar keywords while minimizing potential positional leaks. Finally, we validate the effectiveness and efficiency of FAMI through comprehensive security analysis and experimental simulations.