{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T16:32:26Z","timestamp":1773246746388,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":28,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T00:00:00Z","timestamp":1731542400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,11,14]]},"DOI":"10.1145\/3677052.3698635","type":"proceedings-article","created":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T06:38:06Z","timestamp":1731566286000},"page":"195-203","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Identifying Money Laundering Subgraphs on the Blockchain"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-7103-0301","authenticated-orcid":false,"given":"Kiwhan","family":"Song","sequence":"first","affiliation":[{"name":"MIT, MIT-IBM Watson AI Lab, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0432-853X","authenticated-orcid":false,"given":"Mohamed Ali","family":"Dhraief","sequence":"additional","affiliation":[{"name":"IBM, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5416-3533","authenticated-orcid":false,"given":"Muhua","family":"Xu","sequence":"additional","affiliation":[{"name":"MIT, MIT-IBM Watson AI Lab, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-6440-5989","authenticated-orcid":false,"given":"Locke","family":"Cai","sequence":"additional","affiliation":[{"name":"MIT, MIT-IBM Watson AI Lab, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6470-3387","authenticated-orcid":false,"given":"Xuhao","family":"Chen","sequence":"additional","affiliation":[{"name":"MIT, MIT-IBM Watson AI Lab, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9737-2366","authenticated-orcid":false,"given":"Arvind","family":"Mithal","sequence":"additional","affiliation":[{"name":"MIT, MIT-IBM Watson AI Lab, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0449-6803","authenticated-orcid":false,"given":"Jie","family":"Chen","sequence":"additional","affiliation":[{"name":"IBM Research, MIT-IBM Watson AI Lab, USA"}]}],"member":"320","published-online":{"date-parts":[[2024,11,14]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93037-4_14"},{"key":"e_1_3_2_1_2_1","first-page":"8017","article-title":"Subgraph neural networks","volume":"33","author":"Alsentzer Emily","year":"2020","unstructured":"Emily Alsentzer, Samuel Finlayson, Michelle Li, and Marinka Zitnik. 2020. Subgraph neural networks. Advances in Neural Information Processing Systems 33 (2020), 8017\u20138029.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_3_1","volume-title":"Layer normalization. arXiv preprint arXiv:1607.06450","author":"Ba Jimmy\u00a0Lei","year":"2016","unstructured":"Jimmy\u00a0Lei Ba, Jamie\u00a0Ryan Kiros, and Geoffrey\u00a0E Hinton. 2016. Layer normalization. arXiv preprint arXiv:1607.06450 (2016)."},{"key":"e_1_3_2_1_4_1","volume-title":"KDD Workshop on Machine Learning in Finance.","author":"Bellei Claudio","year":"2024","unstructured":"Claudio Bellei, Muhua Xu, Ross Phillips, Tom Robinson, Mark Weber, Tim Kaler, Charles\u00a0E. Leiserson, Arvind, and Jie Chen. 2024. The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset. In KDD Workshop on Machine Learning in Finance."},{"key":"e_1_3_2_1_5_1","unstructured":"[5] Blockchain.com. 2024. https:\/\/www.blockchain.com\/explorer\/charts\/n-transactions-total"},{"key":"e_1_3_2_1_6_1","volume-title":"International Conference on Machine Learning. PMLR, 1204\u20131215","author":"Cai Tianle","year":"2021","unstructured":"Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-yan Liu, and Liwei Wang. 2021. Graphnorm: A principled approach to accelerating graph neural network training. In International Conference on Machine Learning. PMLR, 1204\u20131215."},{"key":"e_1_3_2_1_7_1","unstructured":"Europol. 2024. The Other Side of the Coin - Analysis of Financial and Economic Crime. https:\/\/www.europol.europa.eu\/cms\/sites\/default\/files\/documents\/The%20Other%20Side%20of%20the%20Coin%20-%20Analysis%20of%20Financial%20and%20Economic%20Crime%20%28EN%29.pdf."},{"key":"e_1_3_2_1_8_1","volume-title":"Proceedings of the thirteenth international conference on artificial intelligence and statistics. JMLR Workshop and Conference Proceedings, 249\u2013256","author":"Glorot Xavier","year":"2010","unstructured":"Xavier Glorot and Yoshua Bengio. 2010. Understanding the difficulty of training deep feedforward neural networks. In Proceedings of the thirteenth international conference on artificial intelligence and statistics. JMLR Workshop and Conference Proceedings, 249\u2013256."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2806416.2806504"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_3_2_1_12_1","volume-title":"Proceedings of Machine Learning and Systems 5","author":"Kaler Tim","year":"2023","unstructured":"Tim Kaler, Alexandros Iliopoulos, Philip Murzynowski, Tao Schardl, Charles\u00a0E Leiserson, and Jie Chen. 2023. Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching. Proceedings of Machine Learning and Systems 5 (2023)."},{"key":"e_1_3_2_1_13_1","first-page":"172","article-title":"Accelerating training and inference of graph neural networks with fast sampling and pipelining","volume":"4","author":"Kaler Tim","year":"2022","unstructured":"Tim Kaler, Nickolas Stathas, Anne Ouyang, Alexandros-Stavros Iliopoulos, Tao Schardl, Charles\u00a0E Leiserson, and Jie Chen. 2022. Accelerating training and inference of graph neural networks with fast sampling and pipelining. Proceedings of Machine Learning and Systems 4 (2022), 172\u2013189.","journal-title":"Proceedings of Machine Learning and Systems"},{"key":"e_1_3_2_1_14_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma P","year":"2014","unstructured":"Diederik\u00a0P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_3_2_1_15_1","volume-title":"Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907","author":"Kipf N","year":"2016","unstructured":"Thomas\u00a0N Kipf and Max Welling. 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)."},{"key":"e_1_3_2_1_16_1","unstructured":"Nasdaq. 2023. Global Financial Crime Report. https:\/\/www.nasdaq.com\/global-financial-crime-report."},{"key":"e_1_3_2_1_17_1","unstructured":"Federal\u00a0Bureau of Investigation. 2023. 2022 Internet Crime Report. https:\/\/www.ic3.gov\/Media\/PDF\/AnnualReport\/2022_IC3Report.pdf."},{"key":"e_1_3_2_1_18_1","unstructured":"U.S.\u00a0Department of\u00a0the Treasury. 2024. 2024 National Money Laundering Risk Assessment. https:\/\/home.treasury.gov\/system\/files\/136\/2024-National-Money-Laundering-Risk-Assessment.pdf."},{"key":"e_1_3_2_1_19_1","volume-title":"BPR: Bayesian personalized ranking from implicit feedback. arXiv preprint arXiv:1205.2618","author":"Rendle Steffen","year":"2012","unstructured":"Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2012. BPR: Bayesian personalized ranking from implicit feedback. arXiv preprint arXiv:1205.2618 (2012)."},{"key":"e_1_3_2_1_20_1","volume-title":"Graph attention networks. arXiv preprint arXiv:1710.10903","author":"Veli\u010dkovi\u0107 Petar","year":"2017","unstructured":"Petar Veli\u010dkovi\u0107, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2017. Graph attention networks. arXiv preprint arXiv:1710.10903 (2017)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_1_22_1","volume-title":"International Conference on Learning Representations.","author":"Wang Xiyuan","year":"2021","unstructured":"Xiyuan Wang and Muhan Zhang. 2021. GLASS: GNN with labeling tricks for subgraph representation learning. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_23_1","volume-title":"Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics. In 2nd KDD Workshop on Anomaly Detection in Finance.","author":"Weber Mark","year":"2019","unstructured":"Mark Weber, Giacomo Domeniconi, Jie Chen, Daniel Karl\u00a0I. Weidele, Claudio Bellei, Tom Robinson, and Charles\u00a0E. Leiserson. 2019. Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics. In 2nd KDD Workshop on Anomaly Detection in Finance."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"e_1_3_2_1_25_1","volume-title":"How powerful are graph neural networks?arXiv preprint arXiv:1810.00826","author":"Xu Keyulu","year":"2018","unstructured":"Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka. 2018. How powerful are graph neural networks?arXiv preprint arXiv:1810.00826 (2018)."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"e_1_3_2_1_27_1","volume-title":"Deep sets. Advances in neural information processing systems 30","author":"Zaheer Manzil","year":"2017","unstructured":"Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Russ\u00a0R Salakhutdinov, and Alexander\u00a0J Smola. 2017. Deep sets. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2021.01.001"}],"event":{"name":"ICAIF '24: 5th ACM International Conference on AI in Finance","location":"Brooklyn NY USA","acronym":"ICAIF '24"},"container-title":["Proceedings of the 5th ACM International Conference on AI in Finance"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3677052.3698635","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3677052.3698635","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T17:12:55Z","timestamp":1755882775000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3677052.3698635"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,14]]},"references-count":28,"alternative-id":["10.1145\/3677052.3698635","10.1145\/3677052"],"URL":"https:\/\/doi.org\/10.1145\/3677052.3698635","relation":{},"subject":[],"published":{"date-parts":[[2024,11,14]]},"assertion":[{"value":"2024-11-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}