{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T12:15:46Z","timestamp":1771330546577,"version":"3.50.1"},"reference-count":36,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,10,6]],"date-time":"2024-10-06T00:00:00Z","timestamp":1728172800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,10,6]],"date-time":"2024-10-06T00:00:00Z","timestamp":1728172800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,10,6]]},"DOI":"10.1109\/dsaa61799.2024.10722808","type":"proceedings-article","created":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T17:23:54Z","timestamp":1729790634000},"page":"1-10","source":"Crossref","is-referenced-by-count":1,"title":["Improving GNN-Based Methods for Scam Detection in Bitcoin Transactions - A Practical Case Study"],"prefix":"10.1109","author":[{"given":"Karanjot Singh","family":"Saggu","sequence":"first","affiliation":[{"name":"University of Ottawa,Faculty of Engineering,Ottawa,Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paula","family":"Branco","sequence":"additional","affiliation":[{"name":"University of Ottawa,Faculty of Engineering,Ottawa,Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guy-Vincent","family":"Jourdan","sequence":"additional","affiliation":[{"name":"University of Ottawa,Faculty of Engineering,Ottawa,Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"issue":"3","key":"ref1","first-page":"100084","article-title":"The \u201cbitcoin generator\u201d scam","volume":"3","author":"Badawi","year":"2022","journal-title":"Blockchain: Research and Applications"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSPW51379.2020.00061"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1609.02907"},{"key":"ref4","first-page":"14501","article-title":"Recipe for a general, powerful, scalable graph transformer","volume":"35","author":"Ramp\u00e1\u0161ek","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref5","volume-title":"Bitcoin hacked transactions 2010\u20132013","author":"Shafiq","year":"2019"},{"key":"ref6","article-title":"Anomaly detection in the bitcoin system-a network perspective","author":"Pham","year":"2016","journal-title":"arXiv preprint"},{"key":"ref7","article-title":"Anti-money laundering in bitcoin: Experimenting with graph convolutional networks for financial foren-sics","author":"Weber","year":"2019","journal-title":"arXiv preprint"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICBC56567.2023.10174963"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-9213-3_14"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2020.3016821"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2008.2005605"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2021.01.001"},{"key":"ref13","article-title":"Graph attention networks","author":"Veli\u010dkovi\u0107","year":"2017","journal-title":"arXiv preprint"},{"key":"ref14","article-title":"Inductive representation learning on large graphs","volume":"30","author":"Hamilton","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-023-00876-4"},{"key":"ref16","first-page":"1204","article-title":"Graphnorm: A principled approach to accelerating graph neural network training","volume-title":"International Conference on Machine Learning","author":"Cai","year":"2021"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11604"},{"key":"ref18","article-title":"Residual gated graph convnets","author":"Bresson","year":"2017","journal-title":"arXiv preprint"},{"key":"ref19","first-page":"4917","article-title":"Towards deeper graph neural networks with differentiable group normalization","volume":"33","author":"Zhou","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3533271.3561793"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3288026"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/DSAA60987.2023.10302516"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICBBE.2009.5163581"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/1879141.1879192"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1214\/10-STS327"},{"key":"ref26","volume-title":"Graph neural networks with learnable structural and positional representations","author":"Dwivedi","year":"2022"},{"key":"ref27","article-title":"Graph neural networks with learnable structural and positional representations","author":"Dwivedi","year":"2021","journal-title":"arXiv preprint"},{"key":"ref28","volume-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"Ioffe","year":"2015"},{"key":"ref29","volume-title":"Graphnorm: A principled approach to accelerating graph neural network training","author":"Cai","year":"2021"},{"key":"ref30","volume-title":"Deepergcn: All you need to train deeper gens","author":"Li","year":"2020"},{"key":"ref31","volume-title":"Graph attention networks","author":"Velickovi\u0107","year":"2018"},{"key":"ref32","volume-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2017"},{"key":"ref33","volume-title":"Recipe for a general, powerful, scalable graph transformer","author":"Ramp\u00e1\u0161ek","year":"2023"},{"key":"ref34","volume-title":"Inductive representation learning on large graphs","author":"Hamilton","year":"2018"},{"key":"ref35","volume-title":"Residual gated graph convnets","author":"Bresson","year":"2018"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.5555\/3294996.3295070"}],"event":{"name":"2024 IEEE 11th International Conference on Data Science and Advanced Analytics (DSAA)","location":"San Diego, CA, USA","start":{"date-parts":[[2024,10,6]]},"end":{"date-parts":[[2024,10,10]]}},"container-title":["2024 IEEE 11th International Conference on Data Science and Advanced Analytics (DSAA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10722027\/10722766\/10722808.pdf?arnumber=10722808","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T02:27:33Z","timestamp":1732674453000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10722808\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,6]]},"references-count":36,"URL":"https:\/\/doi.org\/10.1109\/dsaa61799.2024.10722808","relation":{},"subject":[],"published":{"date-parts":[[2024,10,6]]}}}