Starling: A blockchain-based system for coordinated obstacle mapping in dynamic vehicular environments

Daniel Miehle, Andreas Pfurtscheller, Bernd Bruegge

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Current Vehicle-to-Vehicle solutions cannot ensure the authenticity of safety-critical vehicle and traffic data. Moreover, they do not allow malicious vehicles to be detected and eliminated. However, this is becoming mandatory, as more and more vehicles are on the road and communicating with each other. We propose a system called Starling, which focuses on trusted coordinated obstacle mapping using blockchain technology and a distributed database. Starling enables vehicles to share detected obstacles with other vehicles in a secure and verifiable manner, thus improving road safety. It ensures that data was not manipulated, changed, or deleted and is based on an open protocol so that vehicles can exchange data regardless of their manufacturer. In a case study, we demonstrate how a consensus is reached among vehicles and conduct a comprehensive evaluation of the Starling system using Ethereum and the InterPlanetary File System.

Original languageEnglish
Title of host publicationProceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020
EditorsTung X. Bui
PublisherIEEE Computer Society
Pages4033-4042
Number of pages10
ISBN (Electronic)9780998133133
StatePublished - 2020
Externally publishedYes
Event53rd Annual Hawaii International Conference on System Sciences, HICSS 2020 - Maui, United States
Duration: 7 Jan 202010 Jan 2020

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2020-January
ISSN (Print)1530-1605

Conference

Conference53rd Annual Hawaii International Conference on System Sciences, HICSS 2020
Country/TerritoryUnited States
CityMaui
Period7/01/2010/01/20

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