EVRQ: Achieving Efficient and Verifiable Range Query over Encrypted Traffic Data

Abstract

As a promising solution in boosting the efficiency of urban traffic, intelligent transportation systems (ITS) have been increasingly deployed. Traffic message dissemination, connecting various services and entities, has been regarded as an essential service in ITS, and range query service has also been frequently used for on-demand traffic message retrieval. Meanwhile, as the dataset grows, the service provider tends to outsource the range query services to fog nodes. However, as the fog nodes are not fully trustable, directly outsourcing the services to them may invoke security concerns: on the one hand, the private information, including the traffic messages, query requests, and results should not be revealed to the fog nodes. On the other hand, the fog nodes may return incorrect and/or incomplete query results. Although many schemes have been proposed to achieve privacy-preserving range queries, few of them can support verifiability over dynamic datasets. Therefore, in this paper, we propose an efficient and verifiable range query (EVRQ) scheme over encrypted traffic messages. Specifically, we first build two techniques to respectively enable the fog nodes to efficiently determine and prove whether two rectangles intersect. Then, based on the two approaches and R-tree technique, we create a Merkle R-tree, which we use to build our EVRQ scheme. Security analysis shows that our proposed scheme is really privacy-preserving and can achieve verifiability of the query results. In addition, extensive experiments are conducted, and the results demonstrate that our proposed scheme is indeed efficient.