Integration of blockchain with connected and autonomous vehicles : vision and challenge

Dargahi, T ORCID: https://orcid.org/0000-0002-0908-6483, Ahmadvand, H, Alraja, MN and Yu, C-M 2021, 'Integration of blockchain with connected and autonomous vehicles : vision and challenge' , Journal of Data and Information Quality . (In Press)

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Abstract

Connected and Autonomous Vehicles (CAVs) are introduced to improve individuals’ quality of life by offering a wide range of services. They collect a huge amount of data and exchange them with each other and the infrastructure. The collected data usually includes sensitive information about the users and the surrounding environment. Therefore, data security and privacy are among the main challenges in this industry. Blockchain, an emerging distributed ledger, has been considered by the research community as a potential solution for enhancing data security, integrity and transparency in Intelligent Transportation Systems (ITS). However, despite the emphasis of governments on the transparency of personal data protection practices, CAV stakeholders have not been successful in communicating appropriate information with the end-users regarding the procedure of collecting, storing and processing their personal data, as well as the data ownership. This paper provides a vision of the opportunities and challenges of adopting blockchain in ITS from the “data transparency" and “privacy" perspective. The main aim is to answer the following questions: (1) Considering the amount of personal data collected by the CAVs, such as location, how the integration of blockchain technology would affect transparency, fairness and lawfulness of personal data processing concerning the data subjects (as this is one of the main principles in the existing data protection regulations)? (2) How the trade-off between transparency and privacy can be addressed in blockchain-based ITS use cases?

Item Type: Article
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: Journal of Data and Information Quality
Publisher: Association for Computing Machinery (ACM)
ISSN: 1936-1955
Related URLs:
Funders: UK Royal Society, Research Council (TRC), Sultanate of Oman, Ministry of Science and Technology (MOST), Taiwan
Depositing User: T Dargahi
Date Deposited: 11 Aug 2021 10:57
Last Modified: 28 Aug 2021 10:29
URI: http://usir.salford.ac.uk/id/eprint/61458

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