BeepTrace: Blockchain-enabled Privacy-preserving Contact Tracing for COVID-19 Pandemic and Beyond
Hao Xu, Lei Zhang, Oluwakayode Onireti, Yang Fang, William Bill, Buchanan, Muhammad Ali Imran

TL;DR
BeepTrace introduces a blockchain-based privacy-preserving contact tracing scheme for COVID-19 that enhances security, privacy, and accessibility, encouraging wider adoption and enabling global collaboration in digital contact tracing efforts.
Contribution
The paper presents a novel blockchain-enabled contact tracing scheme that improves privacy, security, and resource efficiency over existing solutions, facilitating widespread adoption and collaboration.
Findings
Higher security and privacy compared to recent solutions
Battery-friendly and globally accessible design
Viable resource requirements for servers and mobile devices
Abstract
The outbreak of COVID-19 pandemic has exposed an urgent need for effective contact tracing solutions through mobile phone applications to prevent the infection from spreading further. However, due to the nature of contact tracing, public concern on privacy issues has been a bottleneck to the existing solutions, which is significantly affecting the uptake of contact tracing applications across the globe. In this paper, we present a blockchain-enabled privacy-preserving contact tracing scheme: BeepTrace, where we propose to adopt blockchain bridging the user/patient and the authorized solvers to desensitize the user ID and location information. Compared with recently proposed contract tracing solutions, our approach shows higher security and privacy with the additional advantages of being battery friendly and globally accessible. Results show viability in terms of the required resource at…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
