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Softw. Eng. Methodol."],"published-print":{"date-parts":[[2025,5,31]]},"abstract":"<jats:p>\n            Ponzi schemes, a form of scam, have been discovered in Ethereum smart contracts in recent years, causing massive financial losses. Existing detection methods primarily focus on rule-based approaches and machine learning techniques that utilize static information as features. However, these methods have significant limitations. Rule-based approaches rely on pre-defined rules with limited capabilities and domain knowledge dependency. Using static information like opcodes for machine learning fails to effectively characterize Ponzi contracts, resulting in poor reliability and interpretability. Our research shows no significant difference between Ponzi and non-Ponzi contracts at the opcode level. Moreover, relying on static information like transactions for machine learning requires a certain number of transactions to achieve detection, which limits the scalability of detection and hinders the identification of\n            <jats:italic>0-day<\/jats:italic>\n            Ponzi schemes.\n          <\/jats:p>\n          <jats:p>\n            In this article, we propose\n            <jats:sc>PonziGuard<\/jats:sc>\n            , an efficient Ponzi scheme detection approach based on contract runtime behavior. Inspired by the observation that a contract\u2019s runtime behavior is more effective in disguising Ponzi contracts from the innocent contracts,\n            <jats:sc>PonziGuard<\/jats:sc>\n            establishes a comprehensive graph representation called\n            <jats:italic>contract runtime behavior graph<\/jats:italic>\n            (CRBG), to accurately depict the behavior of Ponzi contracts. Furthermore, it formulates the detection process as a graph classification task on CRBG, enhancing its overall effectiveness. The experiment results show that\n            <jats:sc>PonziGuard<\/jats:sc>\n            surpasses the current state-of-the-art approaches in the ground-truth dataset, achieving a precision of 96.9%, recall of 98.2%, and F1-score of 97.5%. It also exhibits the highest level of interpretability among the current tools. We applied\n            <jats:sc>PonziGuard<\/jats:sc>\n            to Ethereum Mainnet and demonstrated its effectiveness in real-world scenarios. Using\n            <jats:sc>PonziGuard<\/jats:sc>\n            , we identified 805 Ponzi contracts on Ethereum Mainnet, which have resulted in an estimated economic loss of 281,700 Ether or approximately\n            <jats:inline-formula content-type=\"math\/tex\">\n              <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\($\\)<\/jats:tex-math>\n            <\/jats:inline-formula>\n            500 million USD. We also found\n            <jats:italic>0-day<\/jats:italic>\n            Ponzi schemes in the recently deployed 10,000 smart contracts.\n          <\/jats:p>","DOI":"10.1145\/3707458","type":"journal-article","created":{"date-parts":[[2024,12,10]],"date-time":"2024-12-10T14:56:41Z","timestamp":1733842601000},"page":"1-32","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":23,"title":["Towards Effective Detection of Ponzi Schemes on Ethereum with Contract Runtime Behavior Graph"],"prefix":"10.1145","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-0709-6420","authenticated-orcid":false,"given":"Ruichao","family":"Liang","sequence":"first","affiliation":[{"name":"Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7212-5297","authenticated-orcid":false,"given":"Jing","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0930-0283","authenticated-orcid":false,"given":"Cong","family":"Wu","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3472-419X","authenticated-orcid":false,"given":"Kun","family":"He","sequence":"additional","affiliation":[{"name":"Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1515-3558","authenticated-orcid":false,"given":"Yueming","family":"Wu","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9236-8264","authenticated-orcid":false,"given":"Weisong","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3634-3385","authenticated-orcid":false,"given":"Ruiying","family":"Du","sequence":"additional","affiliation":[{"name":"Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0163-2846","authenticated-orcid":false,"given":"Qingchuan","family":"Zhao","sequence":"additional","affiliation":[{"name":"City University of Hong Kong, Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7300-9215","authenticated-orcid":false,"given":"Yang","family":"Liu","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,4,28]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"Alchemy. 2022. 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