Multi-Receiver Data Authorization With Data Search for Data Sharing in Cloud-Assisted IoV

Publication Name

IEEE Transactions on Intelligent Transportation Systems

Abstract

As technology advances in network technology, the Internet of Vehicles (IoV) has emerged as a prevalent solution for collecting and processing data in Intelligent Transportation Systems (ITS). The Internet of Vehicles (IoV) ecosystem utilizes sensors and interconnected devices to transmit essential information, facilitating effective real-time application deployment. The collected information of sensors is required to be encrypted before uploading to the cloud to protect IoV users' privacy. However, after achieving data confidentiality and authenticity, existing data encryption schemes in IoV have not considered data sharing and data search in the multi-receiver scenarios, such as with various devices in Vehicle-to-Everything (V2X). Retrieval of the needed data accurately from large masses of encrypted data in IoV and then sharing the ciphertext with a group of devices is a challenge that should be solved with priority. To address challenges, this paper makes the first attempt to achieve data sharing and data retrieval at the same time and proposes an efficient multi-receiver data authorization with data search (MR-DADS) scheme in this article. In our MR-DADS, when facing data sharing in IoV, the data owner is able to search the needed encrypted data and then share retrieval results with several IoV devices securely in batches. Furthermore, our scheme utilizes the technique of no pairing encryption technology to reduce the overhead. Then, we demonstrate that the proposed scheme is secure against the Type-I and Type-II adversaries in the random oracle. Finally, the proposed scheme is compared with related works from aspects and the analysis shows our scheme is efficient and practical.

Open Access Status

This publication is not available as open access

Volume

25

Issue

5

First Page

4233

Last Page

4250

Share

COinS
 

Link to publisher version (DOI)

http://dx.doi.org/10.1109/TITS.2023.3328324