Multikeyword-Ranked Search Scheme Supporting Extreme Environments for Internet of Vehicles

In recent years, the cloud infrastructure has been developed as a promising sharing system for the Internet of Vehicles (IoV) communication. During the information exchange, search service over ciphertext called searchable encryption (SE) is an extraordinary method to prevent data breaches. However, two open problems still need to be solved for ranked search, which hinders the application practicality in IoV. First, each data owner must store the extra information to distribute weight values dynamically. Second, ranking in the cloud has not been supported by most existing schemes. In this article, to address the above problems and fit the characteristics of real-time data exchange in IoV, we present a multikeyword-ranked search scheme supporting extreme environments for the IoV. Specifically, our system designs a unique encrypted index tree structure to realize the multikeyword-ranked retrieval, the weight value dynamic adaptive calculation, and dynamic updating in IoV. Moreover, we use a primary-secondary dual-server model to cope with extreme environments and propose a "greedy breadth-first search" algorithm to achieve an effective sublinear search. Finally, comprehensive security analysis and experimental simulation for the proposed system prove that our system can guarantee user privacy and acceptable efficiency.