Εμφάνιση απλής εγγραφής

dc.creatorNegka L., Spathoulas G.en
dc.date.accessioned2023-01-31T09:40:05Z
dc.date.available2023-01-31T09:40:05Z
dc.date.issued2021
dc.identifier10.3390/s21216981
dc.identifier.issn14248220
dc.identifier.urihttp://hdl.handle.net/11615/77133
dc.description.abstractThe automotive industry has been transformed through technological progress during the past decade. Vehicles are equipped with multiple computing devices that offer safety, driving assistance, or multimedia services. Despite these advancements, when an incident occurs, such as a car crash, the involved parties often do not take advantage of the technological capabilities of modern vehicles and attempt to assign liability for the incident to a specific vehicle based upon witness statements. In this paper, we propose a secure, decentralized, blockchain-based platform that can be employed to store encrypted position and velocity values for vehicles in a smart city environment. Such data can be decrypted when the need arises, either through the vehicle driver’s consent or through the consensus of different authorities. The proposed platform also offers an automated way to resolve disputes between involved parties. A simulation has been conducted upon a mobility traffic dataset for a typical day in the city of Cologne to assess the applicability of the proposed methodology to real-world scenarios and the infrastructure requirements that such an application would have. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.en
dc.language.isoenen
dc.sourceSensorsen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85117309756&doi=10.3390%2fs21216981&partnerID=40&md5=f259e8ded7643626f565f4e3ce5211df
dc.subjectAccidentsen
dc.subjectAutomotive industryen
dc.subjectBlockchainen
dc.subjectData privacyen
dc.subjectMultimedia servicesen
dc.subjectBlock-chainen
dc.subjectDecentraliseden
dc.subjectForensicen
dc.subjectForensic analysisen
dc.subjectIntegrityen
dc.subjectPrivacyen
dc.subjectSimulationen
dc.subjectTechnological progressen
dc.subjectTrafficen
dc.subjectVehicularen
dc.subjectVehiclesen
dc.subjectcar drivingen
dc.subjectcomputer simulationen
dc.subjectprivacyen
dc.subjecttechnologyen
dc.subjectAutomobile Drivingen
dc.subjectBlockchainen
dc.subjectComputer Simulationen
dc.subjectPrivacyen
dc.subjectTechnologyen
dc.subjectMDPIen
dc.titleTowards secure, decentralised, and privacy friendly forensic analysis of vehicular dataen
dc.typejournalArticleen


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