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Anomaly Detection on Bitcoin, Ethereum Networks Using GPU-accelerated Machine Learning Methods
Georgia Institute of Technology, Georgia, USA.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
2021 (English)In: 31st International Conference on Computer Theory and Applications, ICCTA 2021: Conference Proceedings, IEEE, 2021, p. 166-171Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
IEEE, 2021. p. 166-171
Keywords [en]
Anomaly Detection, Bitcoin, Blockchain, Cryptocurrency, Ethereum, Fraud, GPU-acceleration, Logistic Regression, Machine Learning, Random Forest, SVM
National Category
Computer Systems Computer Sciences
Identifiers
URN: urn:nbn:se:ltu:diva-94860DOI: 10.1109/ICCTA54562.2021.9916625Scopus ID: 2-s2.0-85141351251OAI: oai:DiVA.org:ltu-94860DiVA, id: diva2:1720204
Conference
31st International Conference on Computer Theory and Applications (ICCTA 2021), Alexandria, Egypt, December 11-13, 2021
Note

ISBN for host publication: 978-1-6654-7854-0

Available from: 2022-12-19 Created: 2022-12-19 Last updated: 2022-12-19Bibliographically approved

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