With the increasing popularity of location-based services(LBS),data outsourcing toward clouds is an emerging paradigm for ease of data management by LBS providers.Geometric range queries are one of the fundamental sea...With the increasing popularity of location-based services(LBS),data outsourcing toward clouds is an emerging paradigm for ease of data management by LBS providers.Geometric range queries are one of the fundamental search functions in LBS,which are to find points inside geometric areas(e.g.,circles or polygons).To ensure data confidentiality,the service users tend to encrypt the data before outsourcing it.However,regarding encrypted data,only a few consider geometric range queries,where the rationale is the high-dimension calculations make these queries particularly harder.In this paper,we propose a novel scheme for geometric range queries,that can provide the privacy of data stored at a cloud server and queries.Our scheme supports querying encrypted spatial data with irregular-shaped areas,achieves fast searches and enables dynamic updates.Experimental results over real-world spatial datasets demonstrate that our scheme results in fewer communication rounds and can speed up the search time 4×compared to state-of-the-art schemes,without carrying any potentially visible leakage in the structure.展开更多
基金supported by National Natural Science Foundation of China(Nos.62072460,62076245,61772538,61772536,61772537,4212022).
文摘With the increasing popularity of location-based services(LBS),data outsourcing toward clouds is an emerging paradigm for ease of data management by LBS providers.Geometric range queries are one of the fundamental search functions in LBS,which are to find points inside geometric areas(e.g.,circles or polygons).To ensure data confidentiality,the service users tend to encrypt the data before outsourcing it.However,regarding encrypted data,only a few consider geometric range queries,where the rationale is the high-dimension calculations make these queries particularly harder.In this paper,we propose a novel scheme for geometric range queries,that can provide the privacy of data stored at a cloud server and queries.Our scheme supports querying encrypted spatial data with irregular-shaped areas,achieves fast searches and enables dynamic updates.Experimental results over real-world spatial datasets demonstrate that our scheme results in fewer communication rounds and can speed up the search time 4×compared to state-of-the-art schemes,without carrying any potentially visible leakage in the structure.
