Efficient and Verifiable Range Query Scheme for Encrypted Geographical Information in Untrusted Cloud Environments

With the rapid development of geo-positioning technologies, location-based services have become increasingly widespread. In the field of location-based services, range queries on geographical data have emerged as an important research topic, attracting significant attention from academia and industry. In many applications, data owners choose to outsource their geographical data and range query tasks to cloud servers to alleviate the burden of local data storage and computation. However, this outsourcing presents many security challenges. These challenges include adversaries analyzing outsourced geographical data and query requests to obtain privacy information, untrusted cloud servers selectively querying a portion of the outsourced data to conserve computational resources, returning incorrect search results to data users, and even illegally modifying the outsourced geographical data, etc. To address these security concerns and provide reliable services to data owners and data users, this paper proposes an efficient and verifiable range query scheme (EVRQ) for encrypted geographical information in untrusted cloud environments. EVRQ is constructed based on a map region tree, 0–1encoding, hash function, Bloom filter, and cryptographic multiset accumulator. Extensive experimental evaluations demonstrate the efficiency of EVRQ, and a comprehensive analysis confirms the security of EVRQ.