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MobileTrust: Secure Knowledge Integration in VANETs.

Hatzivasilis, G., Soultatos, O., Ioannidis, S., Spanoudakis, G., Katos, V. and Demetriou, G., 2020. MobileTrust: Secure Knowledge Integration in VANETs. ACM Transactions on Cyber-Physical Systems, 4 (3), 33.

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DOI: 10.1145/3364181


Vehicular Ad hoc NETworks (VANET) are becoming popular due to the emergence of the Internet of Things and ambient intelligence applications. In such networks, secure resource sharing functionality is accomplished by incorporating trust schemes. Current solutions adopt peer-to-peer technologies that can cover the large operational area. However, these systems fail to capture some inherent properties of VANETs, such as fast and ephemeral interaction, making robust trust evaluation of crowdsourcing challenging. In this article, we propose MobileTrust – a hybrid trust-based system for secure resource sharing in VANETs. The proposal is a breakthrough in centralized trust computing that utilizes cloud and upcoming 5G technologies in order to provide robust trust establishment with global scalability. The ad hoc communication is energy-efficient and protects the system against threats that are not countered by the current settings. To evaluate its performance and effectiveness, MobileTrust is modelled in the SUMO simulator and tested on the traffic features of the small-size German city of Eichstatt. Similar schemes are implemented in the same platform in order to provide a fair comparison. Moreover, MobileTrust is deployed on a typical embedded system platform and applied on a real smart car installation for monitoring traffic and road-state parameters of an urban application. The proposed system is developed under the EU-founded THREAT-ARREST project, to provide security, privacy, and trust in an intelligent and energy-aware transportation scenario, bringing closer the vision of sustainable circular economy.

Item Type:Article
Additional Information:This work has received funding from the European Union Horizon’s 2020 research and innovation programme H2020- DSSC7-2017 under grant agreements No. 786890 (THREAT-ARREST) and No. 830927 (CONCORDIA), as well as the Marie Skodowska-Curie Actions (MSCA) Research and Innovation Staff Exchange (RISE), H2020-MSCA-RISE-2017, under grant agreements No. 777855 (CE-IoT) and No. 778228 (Ideal-Cities)
Group:Faculty of Science & Technology
ID Code:32789
Deposited By: Symplectic RT2
Deposited On:23 Sep 2019 08:47
Last Modified:14 Mar 2022 14:17


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