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Detecting Ponzi Schemes on Ethereum: Towards Healthier Blockchain Technology
Sun Yat-sen University, Guangzhou, China.
Sun Yat-sen University, Guangzhou, China.
Sun Yat-sen University, Guangzhou, China.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
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2018 (English)In: WWW '18: Proceedings of the 2018 World Wide Web Conference, ACM Digital Library, 2018, p. 1409-1418Conference paper, Published paper (Refereed)
Abstract [en]

Blockchain technology becomes increasingly popular. It also attracts scams, for example, Ponzi scheme, a classic fraud, has been found making a notable amount of money on Blockchain, which has a very negative impact. To help dealing with this issue, this paper proposes an approach to detect Ponzi schemes on blockchain by using data mining and machine learning methods. By verifying smart contracts on Ethereum, we first extract features from user accounts and operation codes of the smart contracts and then build a classification model to detect latent Ponzi schemes implemented as smart contracts. The experimental results show that the proposed approach can achieve high accuracy for practical use. More importantly, the approach can be used to detect Ponzi schemes even at the moment of its creation. By using the proposed approach, we estimate that there are more than 400 Ponzi schemes running on Ethereum. Based on these results, we propose to build a uniform platform to evaluate and monitor every created smart contract for early warning of scams.

Place, publisher, year, edition, pages
ACM Digital Library, 2018. p. 1409-1418
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:uu:diva-366224DOI: 10.1145/3178876.3186046ISI: 000460379000138ISBN: 978-1-4503-5639-8 (electronic)OAI: oai:DiVA.org:uu-366224DiVA, id: diva2:1263913
Conference
World Wide Web Conference (TheWebConf 2018), April 23 - 27 2018, Lyon, France
Projects
STINT Blockchain
Funder
The Swedish Foundation for International Cooperation in Research and Higher Education (STINT)Available from: 2018-11-18 Created: 2018-11-18 Last updated: 2019-04-10Bibliographically approved

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Ngai, Edith

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