Abstract
In the cloud-based vehicular ad-hoc network (VANET), massive vehicle information is stored on the cloud, and a large amount of data query, calculation, monitoring, and management are carried out at all times. The secure spatial query methods in VANET allow authorized users to convert the original spatial query to encrypted spatial query, which is called query token and will be processed in ciphertext mode by the service provider. Thus, the service provider learns which encrypted records are returned as the result of a query, which is defined as the access pattern. Since only the correct query results that match the query tokens are returned, the service provider can observe which encrypted data are accessed and returned to the client when a query is launched clearly, and it leads to the leakage of data access pattern. In this paper, a reconstruction attack scheme is proposed, which utilizes the access patterns in the secure query processes, and then it reconstructs the index of outsourced spatial data that are collected from the vehicles. The proposed scheme proves the security threats in the VANET. Extensive experiments on real-world datasets demonstrate that our attack scheme can achieve quite a high reconstruction rate.
Highlights
At present, the vehicular ad-hoc network (VANET) has gained a lot of attention in the field of intelligent transportation. e VANET can be used to intelligently control the traffic process, such as real-time traffic information systems to ensure traffic efficiency, and vehicle safety systems, such as rear-end collision warning systems, to improve vehicle safety
In the searchable encryption mechanism, the search process for encrypted files is as follows: First, the authorized user will submit the query token to the service provider, who will process the query through a series of calculations and return the query result to the user in the form of ciphertext. en, the user decrypts the query result locally
We propose a reconstruction attack scheme on outsourced spatial dataset using access pattern leakage in VANET systems. e threat model considered is as follows
Summary
The vehicular ad-hoc network (VANET) has gained a lot of attention in the field of intelligent transportation. e VANET can be used to intelligently control the traffic process, such as real-time traffic information systems to ensure traffic efficiency, and vehicle safety systems, such as rear-end collision warning systems, to improve vehicle safety. Exploiting the collusion of the service provider and the secondary user, a set of selected range queries are injected into the dataset, and through the access patterns of these queries, the dataset index is completely reconstructed. We propose a reconstruction attack scheme on outsourced spatial dataset using access pattern leakage in VANET systems. Assuming that the service provider only has a little prior knowledge of the spatial dataset and the users will issue enough one-dimensional and uniform queries to the server, our reconstruction attack will be processed as the following four steps. (i) A reconstruction attack against secure outsourced spatial dataset in VANET systems is proposed, proving that the security threats caused by access pattern leakage are universal. (iii) Extensive experiments on real-world datasets demonstrate that our attack scheme can achieve quite a high reconstruction rate
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