{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T16:47:52Z","timestamp":1784134072202,"version":"3.55.0"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Napier Technologies Ltd"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/access.2022.3167699","type":"journal-article","created":{"date-parts":[[2022,4,18]],"date-time":"2022-04-18T20:13:24Z","timestamp":1650312804000},"page":"41720-41739","source":"Crossref","is-referenced-by-count":38,"title":["Amaretto: An Active Learning Framework for Money Laundering Detection"],"prefix":"10.1109","volume":"10","author":[{"given":"Danilo","family":"Labanca","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luca","family":"Primerano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0419-9200","authenticated-orcid":false,"given":"Marcus","family":"Markland-Montgomery","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mario","family":"Polino","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8284-6074","authenticated-orcid":false,"given":"Michele","family":"Carminati","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4710-5283","authenticated-orcid":false,"given":"Stefano","family":"Zanero","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","volume-title":"Estimating Illicit Financial Flows Resulting From Drug Trafficking and Other Transnational Organized Crimes","year":"2011"},{"key":"ref2","volume-title":"Outliers in Statistical Data","author":"Barnett","year":"1994"},{"key":"ref3","volume-title":"Guidance for a Risk-Based Approach: Securities Sector","year":"2018"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1108\/PAR-06-2019-0065"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-017-1144-z"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-3075-3_5"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1108\/JMLC-02-2020-0018"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2010.08.006"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2015.09.005"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/WICOM.2007.1352"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3086230"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/342009.335437"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2002.1184035"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2015.04.002"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-55415-5_32"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93411-2_10"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3178370"},{"key":"ref19","first-page":"285","article-title":"Evasion attacks against banking fraud detection systems","volume-title":"Proc. 23rd Int. Symp. Res. Attacks, Intrusions Defenses (RAID)","author":"Carminati"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-61702-8_6"},{"key":"ref21","first-page":"89","article-title":"Counter terrorism finance by detecting money laundering hidden networks using unsupervised machine learning algorithm","volume-title":"Proc. Int. Conf. ICT, Soc., Hum. Beings","author":"Shokry"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2010.66"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/DBKDA.2010.27"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA51294.2020.00047"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2016.0172"},{"key":"ref26","article-title":"Adaptive machine learning for credit card fraud detection","author":"Pozzolo","year":"2015"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2010.08.008"},{"issue":"4","key":"ref28","first-page":"21","article-title":"Financial crimes enforcement network AI system (FAIS) identifying potential money laundering from reports of large cash transactions","volume-title":"AI Mag.","volume":"16","author":"Senator","year":"1995"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1108\/JMLC-04-2020-0033"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1108\/JMLC-07-2019-0055"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-64466-6_3"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113318"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/s42979-021-00558-z"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3052313"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1613\/jair.3623"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-60080-2_17"},{"key":"ref37","first-page":"49","article-title":"Ai2: Training a big data machine to defend","volume-title":"Proc. 2nd IEEE Int. Conf. Big Data Secur. Cloud (BigDataSecurity), IEEE Int. Conf. High Perform. Smart Comput. (HPSC), IEEE Int. Conf. Intell. Data Secur. (IDS)","author":"Veeramachaneni"},{"key":"ref38","article-title":"Active anomaly detection via ensembles: Insights, algorithms, and interpretability","author":"Das","year":"2019","journal-title":"arXiv:1901.08930"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3409073.3409080"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-014-0365-y"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.3233\/IDA-2007-11606"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/956750.956831"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1103\/physreva.45.6056"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/BF00116251"},{"issue":"1","key":"ref45","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-37456-2_14"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2017.12"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/0925-2312(95)00039-9"},{"key":"ref49","first-page":"2960","article-title":"Practical Bayesian optimization of machine learning algorithms","volume-title":"Proc. 26th Annu. Conf. Neural Inf. Process. Syst.","author":"Snoek"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-008-0116-z"},{"key":"ref51","first-page":"1","article-title":"Auto-encoding variational Bayes","volume-title":"Proc. 2nd Int. Conf. Learn. Represent. (ICLR)","author":"Kingma"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2947676"},{"key":"ref53","first-page":"172","article-title":"A novel anomaly detection scheme based on principal component classifier","volume-title":"Proc. IEEE Found. New Directions Data Mining Workshop, Conjunction 3rd IEEE Int. Conf. Data Mining (ICDM","author":"Shyu"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref55","first-page":"4765","article-title":"A unified approach to interpreting model predictions","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Lundberg"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.3321\/j.issn:0529-6579.2007.z1.029"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9668973\/09758694.pdf?arnumber=9758694","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T20:38:55Z","timestamp":1705955935000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9758694\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":56,"URL":"https:\/\/doi.org\/10.1109\/access.2022.3167699","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}