Reliable and Secure Distributed Smart Road Pricing System for Smart Cities

Vehicular networks have emerged as a promising technology for the development of traffic management systems in smart cities. They are expected to revolutionize a variety of applications such as traffic monitoring and pay-as-you-drive services. Recently, the notion of road pricing has become crucial...

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Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems 2019-05, Vol.20 (5), p.1592-1603
Main Authors: Bouchelaghem, Siham, Omar, Mawloud
Format: Article
Language:English
Subjects:
Ad hoc networks
Cameras
Computer Science
Cryptography
Geology
Management systems
Pricing
Privacy
Road use pricing
Roads
Security
smart cities
Smart roads
SRP
toll evasion
Toll roads
Tolls
Traffic congestion
Traffic management
Vehicles
Vehicular networks
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Summary:Vehicular networks have emerged as a promising technology for the development of traffic management systems in smart cities. They are expected to revolutionize a variety of applications such as traffic monitoring and pay-as-you-drive services. Recently, the notion of road pricing has become crucial in most big cities as it contributes in road congestion avoidance, fuel consumption saving, and pollution reduction. However, as the road pricing systems need trip data to invoice citizens, it is vital to ensure geolocation privacy while keeping drivers honest. In this paper, we propose a security approach for smart road pricing systems, which prevents toll evasion violations. The proposed approach operates under a fully distributed threshold-based control system to detect fraudulent drivers trying to cheat on their tolls. The accused drivers are reported to the toll server in order to take the appropriate countermeasures. Through the security analysis, we show the robustness of the proposed approach against a range of potential attacks. We also evaluate the proposed approach through simulations considering important metrics, namely, the storage and communication overheads. The proposed approach shows better performance results in comparison to the existing approaches. Furthermore, we evaluate the proposed approach efficiency in terms of detection precision, where it demonstrates promising results.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2018.2842754