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Title Goliath: A Decentralized Framework For Data Collection In Intelligent Transportation Systems
ID_Doc 28131
Authors Maffiola D.; Longari S.; Carminati M.; Tanelli M.; Zanero S.
Year 2022
Published IEEE Transactions on Intelligent Transportation Systems, 23, 8
DOI http://dx.doi.org/10.1109/TITS.2021.3123824
Abstract Intelligent Transportation Systems (ITSs) technology has advanced during the past years, and it is now used for several applications that require vehicles to exchange real-time data, such as in traffic information management. Traditionally, road traffic information has been collected using on-site sensors. However, crowd-sourcing traffic information from onboard sensors or smartphones has become a viable alternative. State-of-the-art solutions currently follow a centralized model where only the service provider has complete access to the collected traffic data and represent a single point of failure and trust. In this paper, we propose GOLIATH, a blockchain-based decentralized framework that runs on the In-Vehicle Infotainment (IVI) system to collect real-time information exchanged between the network's participants. Our approach mitigates the limitations of existing crowd-sourcing centralized solutions by guaranteeing trusted information collection and exchange, fully exploiting the intrinsic distributed nature of vehicles. We demonstrate its feasibility in the context of vehicle positioning and traffic information management. Each vehicle participating in the decentralized network shares its position and neighbors' ones in the form of a transaction recorded on the ledger, which uses a novel consensus mechanism to validate it. We design the consensus mechanism resilient against a realistic set of adversaries that aim to tamper or disable the communication. We evaluate the proposed framework in a simulated (but realistic) environment, which considers different threats and allows showing its robustness and safety properties. © 2000-2011 IEEE.
Author Keywords Automotive; Blockchain; Positioning systems; Smart cities; Traffic management


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