{"id":"https://openalex.org/W3167198684","doi":"https://doi.org/10.1109/access.2021.3086359","title":"Variational Autoencoders and Wasserstein Generative Adversarial Networks for Improving the Anti-Money Laundering Process","display_name":"Variational Autoencoders and Wasserstein Generative Adversarial Networks for Improving the Anti-Money Laundering Process","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3167198684","doi":"https://doi.org/10.1109/access.2021.3086359","mag":"3167198684"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3086359","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3086359","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09446893.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09446893.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100438512","display_name":"Zhiyuan Chen","orcid":"https://orcid.org/0000-0002-4915-1593"},"institutions":[{"id":"https://openalex.org/I155043079","display_name":"University of Nottingham Malaysia Campus","ror":"https://ror.org/04mz9mt17","country_code":"MY","type":"education","lineage":["https://openalex.org/I142263535","https://openalex.org/I155043079"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Zhiyuan Chen","raw_affiliation_strings":["School of Computer Science, University of Nottingham Malaysia, Semenyih, Malaysia"],"raw_orcid":"https://orcid.org/0000-0002-4915-1593","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Nottingham Malaysia, Semenyih, Malaysia","institution_ids":["https://openalex.org/I155043079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020936588","display_name":"Waleed Mahmoud Soliman","orcid":"https://orcid.org/0000-0003-1855-1137"},"institutions":[{"id":"https://openalex.org/I155043079","display_name":"University of Nottingham Malaysia Campus","ror":"https://ror.org/04mz9mt17","country_code":"MY","type":"education","lineage":["https://openalex.org/I142263535","https://openalex.org/I155043079"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Waleed Mahmoud Soliman","raw_affiliation_strings":["School of Computer Science, University of Nottingham Malaysia, Semenyih, Malaysia"],"raw_orcid":"https://orcid.org/0000-0003-1855-1137","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Nottingham Malaysia, Semenyih, Malaysia","institution_ids":["https://openalex.org/I155043079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042617322","display_name":"Amril Nazir","orcid":"https://orcid.org/0000-0001-7116-7607"},"institutions":[{"id":"https://openalex.org/I91044093","display_name":"Zayed University","ror":"https://ror.org/03snqfa66","country_code":"AE","type":"education","lineage":["https://openalex.org/I91044093"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Amril Nazir","raw_affiliation_strings":["College of Technological Innovation, Zayed University, Abu Dhabi, United Arab Emirates"],"raw_orcid":"https://orcid.org/0000-0001-7116-7607","affiliations":[{"raw_affiliation_string":"College of Technological Innovation, Zayed University, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I91044093"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039552087","display_name":"Mohammad Shorfuzzaman","orcid":"https://orcid.org/0000-0002-8050-8431"},"institutions":[{"id":"https://openalex.org/I179331831","display_name":"Taif University","ror":"https://ror.org/014g1a453","country_code":"SA","type":"education","lineage":["https://openalex.org/I179331831"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Mohammad Shorfuzzaman","raw_affiliation_strings":["College of Computers and Information Technology, Taif University, Ta\u2019if, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-8050-8431","affiliations":[{"raw_affiliation_string":"College of Computers and Information Technology, Taif University, Ta\u2019if, Saudi Arabia","institution_ids":["https://openalex.org/I179331831"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100438512"],"corresponding_institution_ids":["https://openalex.org/I155043079"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":9.908,"has_fulltext":true,"cited_by_count":44,"citation_normalized_percentile":{"value":0.97875375,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"9","issue":null,"first_page":"83762","last_page":"83785"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11838","display_name":"Crime, Illicit Activities, and Governance","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11838","display_name":"Crime, Illicit Activities, and Governance","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9199743270874023},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8263076543807983},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6207971572875977},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5999729633331299},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5864187479019165},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.557315468788147},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5423880219459534},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5350296497344971},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5303162932395935},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4930708110332489},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.47512751817703247},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.43724051117897034},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4327709674835205},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4070143401622772},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40076425671577454}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9199743270874023},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8263076543807983},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6207971572875977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5999729633331299},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5864187479019165},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.557315468788147},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5423880219459534},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5350296497344971},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5303162932395935},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4930708110332489},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.47512751817703247},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.43724051117897034},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4327709674835205},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4070143401622772},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40076425671577454},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3086359","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3086359","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09446893.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9b2b0b79b77c48888048ffa16e2abb04","is_oa":true,"landing_page_url":"https://doaj.org/article/9b2b0b79b77c48888048ffa16e2abb04","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 83762-83785 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3086359","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3086359","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09446893.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8299999833106995,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G6905075233","display_name":null,"funder_award_id":"TURSP-2020/79","funder_id":"https://openalex.org/F4320323722","funder_display_name":"Taif University"},{"id":"https://openalex.org/G7299194679","display_name":null,"funder_award_id":"TURSP-2020","funder_id":"https://openalex.org/F4320323722","funder_display_name":"Taif University"}],"funders":[{"id":"https://openalex.org/F4320323722","display_name":"Taif University","ror":"https://ror.org/014g1a453"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3167198684.pdf","grobid_xml":"https://content.openalex.org/works/W3167198684.grobid-xml"},"referenced_works_count":66,"referenced_works":["https://openalex.org/W83466286","https://openalex.org/W89129796","https://openalex.org/W1710476689","https://openalex.org/W1959608418","https://openalex.org/W1978424198","https://openalex.org/W1990179744","https://openalex.org/W1998626065","https://openalex.org/W2004820431","https://openalex.org/W2097882134","https://openalex.org/W2107689792","https://openalex.org/W2118341639","https://openalex.org/W2118360154","https://openalex.org/W2138855256","https://openalex.org/W2148740744","https://openalex.org/W2163952039","https://openalex.org/W2258973708","https://openalex.org/W2272215152","https://openalex.org/W2314555762","https://openalex.org/W2396932848","https://openalex.org/W2483907835","https://openalex.org/W2522834812","https://openalex.org/W2585169518","https://openalex.org/W2616431611","https://openalex.org/W2739748921","https://openalex.org/W2767852759","https://openalex.org/W2786146442","https://openalex.org/W2788185337","https://openalex.org/W2788487394","https://openalex.org/W2788688855","https://openalex.org/W2790097716","https://openalex.org/W2802778367","https://openalex.org/W2809211248","https://openalex.org/W2898514850","https://openalex.org/W2903503362","https://openalex.org/W2910109950","https://openalex.org/W2987299728","https://openalex.org/W2993951199","https://openalex.org/W2997877353","https://openalex.org/W3048072784","https://openalex.org/W3118991287","https://openalex.org/W3153872861","https://openalex.org/W3210406898","https://openalex.org/W4245119036","https://openalex.org/W4288028692","https://openalex.org/W4297894630","https://openalex.org/W4298289240","https://openalex.org/W4298858155","https://openalex.org/W6637568146","https://openalex.org/W6640963894","https://openalex.org/W6644880718","https://openalex.org/W6677578155","https://openalex.org/W6680435780","https://openalex.org/W6692302727","https://openalex.org/W6712104533","https://openalex.org/W6722017125","https://openalex.org/W6738132598","https://openalex.org/W6741832134","https://openalex.org/W6751469297","https://openalex.org/W6758108085","https://openalex.org/W6769775441","https://openalex.org/W6770782907","https://openalex.org/W6772470102","https://openalex.org/W6781719484","https://openalex.org/W6787876374","https://openalex.org/W7016021835","https://openalex.org/W7046357184"],"related_works":["https://openalex.org/W2997921738","https://openalex.org/W2470043383","https://openalex.org/W2965146396","https://openalex.org/W2953501176","https://openalex.org/W2965095304","https://openalex.org/W3034474024","https://openalex.org/W4385421777","https://openalex.org/W4317242571","https://openalex.org/W2944085132","https://openalex.org/W2770818364"],"abstract_inverted_index":{"There":[0],"has":[1],"been":[2],"much":[3],"recent":[4],"work":[5],"on":[6,23],"fraud":[7,42,100,142,154,248],"and":[8,61,90,99,119,180,192],"Anti":[9],"Money":[10],"Laundering":[11],"(AML)":[12],"detection":[13,82,101],"using":[14],"machine":[15],"learning":[16,52,92,112],"techniques.":[17,25],"However,":[18],"most":[19],"algorithms":[20],"are":[21,157,174],"based":[22],"supervised":[24,29],"Studies":[26],"show":[27],"that":[28,217],"techniques":[30,70,93],"often":[31],"have":[32,54,72],"the":[33,45,73,126,131,161,178,188,200,211,218,231,247],"limitation":[34],"of":[35,75,88,187,198,242,246],"not":[36,76],"adapting":[37],"well":[38],"to":[39,58,79,94,103,129,139,152,164,176,225],"new":[40,65],"irregular":[41,62],"patterns":[43,63],"when":[44],"dataset":[46,128,163],"is":[47,150],"highly":[48],"imbalanced.":[49],"Instead,":[50],"unsupervised":[51,69,89],"can":[53],"a":[55,86,120,166,195],"better":[56],"capability":[57],"find":[59],"anomalous":[60],"in":[64,230],"transaction.":[66],"Despite":[67],"this,":[68],"also":[71],"disadvantage":[74],"being":[77],"able":[78],"give":[80],"state-of-the-art":[81],"results.":[83],"We":[84,124,183],"propose":[85],"suite":[87],"deep":[91,111],"implement":[95],"an":[96,240],"anti-money":[97],"laundering":[98],"system":[102,108],"resolve":[104],"this":[105],"limitation.":[106],"The":[107],"leverages":[109],"three":[110],"models:":[113],"autoencoder":[114,117],"(AE),":[115],"variational":[116],"(VAE),":[118],"generative":[121],"adversarial":[122],"network.":[123],"preprocess":[125],"given":[127],"separate":[130],"Transaction":[132],"Date":[133],"attribute":[134],"into":[135],"its":[136],"base":[137,162],"components":[138],"capture":[140],"time-related":[141],"patterns.":[143],"Also,":[144],"Wasserstein":[145],"Generative":[146],"Adversarial":[147],"Network":[148],"(WGAN)":[149],"used":[151,175],"generate":[153],"transactions,":[155],"which":[156,208],"then":[158],"mixed":[159,169],"with":[160,244],"form":[165],"more":[167],"balanced":[168],"dataset.":[170],"These":[171],"two":[172,185],"datasets":[173],"train":[177],"AE":[179,189,234],"VAE":[181],"models.":[182],"built":[184],"versions":[186],"model":[190],"(single-loss":[191],"multi-loss)":[193],"besides":[194],"novel":[196],"method":[197],"calculating":[199],"anomaly":[201],"score":[202],"threshold,":[203],"called":[204],"Recall-First":[205],"Threshold":[206],"(RFT),":[207],"helps":[209],"enhance":[210],"model's":[212],"performance.":[213],"Experimental":[214],"results":[215],"demonstrated":[216],"False":[219],"Positive":[220],"Rate":[221],"(FPR)":[222],"drops":[223],"down":[224],"as":[226,228],"low":[227],"7%":[229],"proposed":[232],"multi-loss":[233],"model.":[235],"In":[236],"comparison,":[237],"we":[238],"achieved":[239],"accuracy":[241],"93%,":[243],"100%":[245],"transactions":[249],"recalled":[250],"successfully.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8}],"updated_date":"2026-05-28T09:10:13.091523","created_date":"2025-10-10T00:00:00"}