Secure and Privacy-Preserving Aggregation Scheme for Traffic Management Systems
Document Type
Conference Proceeding
Publication Date
9-16-2023
School
Computing Sciences and Computer Engineering
Abstract
Traffic delays and congestion will likely worsen as cars on the road rise. Autonomous vehicles (AVs) can help solve these problems by reporting their routes’ information to control traffic congestion. However, current route reporting schemes ask AV users to disclose their route’s information, which breaches the user’s privacy. In this paper, we offer an aggregation over encrypted data technique for traffic management systems to solve the difficulty of privacy-preserving route reporting for AV users. The area of interest is divided into several groups/communities. Every community will be controlled by a road-side-unit (RSU) to collect and aggregate the route information for the AVs inside its group/community. In addition, we used a group signature scheme to ensure the membership of the AV within the group/community without disclosing its real identity. Our security and privacy analysis show that our proposed scheme can achieve the required design goals. Also, our performance evaluation shows that our scheme achieves low communication and computation overheads.
Publication Title
2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things
Recommended Citation
Madububambachu, U.,
White, K.,
Sibeudu, K.,
Sherif, A.,
Elsersy, M.
(2023). Secure and Privacy-Preserving Aggregation Scheme for Traffic Management Systems. 2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things.
Available at: https://aquila.usm.edu/fac_pubs/21753
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