{"id":"https://openalex.org/W7148551840","doi":"https://doi.org/10.1109/access.2026.3680136","title":"Hybrid Generative Adversarial Network Assisted Oversampling for Credit Card Fraud Detection","display_name":"Hybrid Generative Adversarial Network Assisted Oversampling for Credit Card Fraud Detection","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7148551840","doi":"https://doi.org/10.1109/access.2026.3680136"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3680136","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3680136","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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://doi.org/10.1109/access.2026.3680136","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019747299","display_name":"Eman Abdullah Aldakheel","orcid":"https://orcid.org/0000-0002-4035-7763"},"institutions":[{"id":"https://openalex.org/I106778892","display_name":"Princess Nourah bint Abdulrahman University","ror":"https://ror.org/05b0cyh02","country_code":"SA","type":"education","lineage":["https://openalex.org/I106778892"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Eman Abdullah Aldakheel","raw_affiliation_strings":["Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-4035-7763","affiliations":[{"raw_affiliation_string":"Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I106778892"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102900347","display_name":"Ahmed M. Osman","orcid":"https://orcid.org/0009-0002-0527-533X"},"institutions":[{"id":"https://openalex.org/I130009713","display_name":"Suez University","ror":"https://ror.org/00ndhrx30","country_code":"EG","type":"education","lineage":["https://openalex.org/I130009713"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Ahmed M. Osman","raw_affiliation_strings":["Department of Information Systems, Faculty of Computers and Information, Suez University, P.O.Box:43221, Suez, Egypt"],"raw_orcid":"https://orcid.org/0009-0002-0527-533X","affiliations":[{"raw_affiliation_string":"Department of Information Systems, Faculty of Computers and Information, Suez University, P.O.Box:43221, Suez, Egypt","institution_ids":["https://openalex.org/I130009713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042388205","display_name":"Safia Abbas","orcid":"https://orcid.org/0000-0002-2873-2006"},"institutions":[{"id":"https://openalex.org/I107720978","display_name":"Ain Shams University","ror":"https://ror.org/00cb9w016","country_code":"EG","type":"education","lineage":["https://openalex.org/I107720978"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Safia Abbas","raw_affiliation_strings":["Department of Computer Science, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt"],"raw_orcid":"https://orcid.org/0000-0002-2873-2006","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt","institution_ids":["https://openalex.org/I107720978"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132775896","display_name":"Yasser Fouad","orcid":null},"institutions":[{"id":"https://openalex.org/I130009713","display_name":"Suez University","ror":"https://ror.org/00ndhrx30","country_code":"EG","type":"education","lineage":["https://openalex.org/I130009713"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Yasser Fouad","raw_affiliation_strings":["Department of Computer Science, Faculty of Computers and Information, Suez University, P.O.Box:43221, Suez, Egypt"],"raw_orcid":"https://orcid.org/0009-0001-2802-080X","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Faculty of Computers and Information, Suez University, P.O.Box:43221, Suez, Egypt","institution_ids":["https://openalex.org/I130009713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014096185","display_name":"Ahmed M. Elshewey","orcid":"https://orcid.org/0000-0002-3048-1920"},"institutions":[{"id":"https://openalex.org/I130009713","display_name":"Suez University","ror":"https://ror.org/00ndhrx30","country_code":"EG","type":"education","lineage":["https://openalex.org/I130009713"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Ahmed M. Elshewey","raw_affiliation_strings":["Department of Computer Science, Faculty of Computers and Information, Suez University, P.O.Box:43221, Suez, Egypt"],"raw_orcid":"https://orcid.org/0000-0002-3048-1920","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Faculty of Computers and Information, Suez University, P.O.Box:43221, Suez, Egypt","institution_ids":["https://openalex.org/I130009713"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5019747299"],"corresponding_institution_ids":["https://openalex.org/I106778892"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.67881451,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9215999841690063,"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"}},"topics":[{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9215999841690063,"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/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.028599999845027924,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.002099999925121665,"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/oversampling","display_name":"Oversampling","score":0.8217999935150146},{"id":"https://openalex.org/keywords/credit-card-fraud","display_name":"Credit card fraud","score":0.8205000162124634},{"id":"https://openalex.org/keywords/credit-card","display_name":"Credit card","score":0.7631999850273132},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7354000210762024},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.47040000557899475}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8281999826431274},{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.8217999935150146},{"id":"https://openalex.org/C2780747020","wikidata":"https://www.wikidata.org/wiki/Q83873","display_name":"Credit card fraud","level":4,"score":0.8205000162124634},{"id":"https://openalex.org/C2983355114","wikidata":"https://www.wikidata.org/wiki/Q161380","display_name":"Credit card","level":3,"score":0.7631999850273132},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7354000210762024},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4952000081539154},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.47040000557899475},{"id":"https://openalex.org/C110406131","wikidata":"https://www.wikidata.org/wiki/Q41349","display_name":"Smart card","level":2,"score":0.41040000319480896},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.39719998836517334},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35260000824928284},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3467000126838684},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3102000057697296},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27649998664855957}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3680136","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3680136","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7d50c3a760d34b2fb32e63628c80ef9c","is_oa":true,"landing_page_url":"https://doaj.org/article/7d50c3a760d34b2fb32e63628c80ef9c","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 14, Pp 54828-54845 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3680136","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3680136","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.5700737833976746,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G5615491","display_name":null,"funder_award_id":"PNURSP2025R409","funder_id":"https://openalex.org/F4320322484","funder_display_name":"Princess Nourah Bint Abdulrahman University"}],"funders":[{"id":"https://openalex.org/F4320322484","display_name":"Princess Nourah Bint Abdulrahman University","ror":"https://ror.org/05b0cyh02"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Credit-card":[0],"fraud":[1,127],"detection":[2],"is":[3,65,98,145,284,301],"a":[4,21,60,74,84,112,118,139,226,247],"challenging":[5],"task":[6],"due":[7],"to":[8,106,123,137,147,179,239,243,261,306],"the":[9,25,35,63,69,79,90,102,131,167,181,187,262,269],"highly":[10],"imbalanced":[11],"nature":[12],"of":[13,24,49,202,205,208,211,214,218,229,250],"real-world":[14],"transaction":[15],"data,":[16],"where":[17,282],"fraudulent":[18],"cases":[19],"constitute":[20],"tiny":[22],"fraction":[23],"total.":[26],"In":[27],"this":[28,32],"study,":[29],"we":[30],"address":[31],"challenge":[33],"using":[34,100],"publicly":[36,302],"available":[37,303],"Credit":[38],"Card":[39],"Fraud":[40],"Detection":[41],"dataset":[42,64],"from":[43,176],"Kaggle,":[44],"which":[45,50],"contains":[46],"284,807":[47],"transactions,":[48],"only":[51,101],"about":[52],"0.17%":[53],"are":[54,164],"labeled":[55],"as":[56,73],"fraudulent.":[57],"To":[58],"ensure":[59,307],"realistic":[61,125],"evaluation,":[62,297],"split":[66,82],"chronologically,":[67],"with":[68,89,171,196,225,232,253],"last":[70],"20%":[71],"reserved":[72],"hold-out":[75],"test":[76],"set,":[77,88,170],"and":[78,86,159,216,241,258,276,298,310],"remaining":[80],"80%":[81],"into":[83],"training":[85,103,169],"validation":[87,177],"final":[91],"10%":[92],"used":[93],"for":[94],"validation.":[95],"Feature":[96],"preprocessing":[97],"performed":[99],"set":[104],"statistics":[105],"prevent":[107],"information":[108],"leakage.":[109],"We":[110],"propose":[111],"hybrid":[113,222,270,294],"data-balancing":[114],"framework":[115],"that":[116,186,268],"integrates":[117],"Generative":[119],"Adversarial":[120],"Network":[121],"(GAN)":[122],"generate":[124],"synthetic":[126,153],"samples,":[128],"followed":[129],"by":[130],"Synthetic":[132],"Minority":[133],"Oversampling":[134],"Technique":[135],"(SMOTE)":[136],"achieve":[138],"target":[140,227],"minority-to-majority":[141],"ratio.":[142],"This":[143],"approach":[144],"designed":[146],"improve":[148],"minority":[149],"representation":[150],"while":[151,245],"limiting":[152],"noise":[154],"through":[155],"GAN":[156,292],"early":[157],"stopping":[158],"balanced":[160],"sample":[161],"generation.":[162],"Classifiers":[163],"trained":[165],"on":[166],"resampled":[168],"optimal":[172],"decision":[173],"thresholds":[174],"determined":[175],"data":[178,290],"maximize":[180],"F1-score.":[182],"Experimental":[183],"results":[184,266],"show":[185],"best":[188],"Baseline":[189],"without":[190],"oversampling":[191,271],"\u2014a":[192],"Random":[193,235],"Forest":[194],"model":[195,296],"class":[197],"weighting":[198],"\u2014achieves":[199],"an":[200,233],"accuracy":[201],"0.999596,":[203],"precision":[204,257],"0.9333,":[206],"recall":[207,238,283],"0.7467,":[209],"F1-score":[210,259],"0.8296,":[212],"ROC-AUC":[213,242],"0.9556,":[215],"PR-AUC":[217,249],"0.8037.":[219],"Our":[220],"proposed":[221],"method,":[223],"GAN+SMOTE":[224],"ratio":[228],"0.35,":[230],"combined":[231],"unweighted":[234],"Forest,":[236],"improves":[237],"0.7733":[240],"0.9762":[244],"maintaining":[246],"comparable":[248],"0.8003,":[251],"though":[252],"slight":[254],"reductions":[255],"in":[256,280],"compared":[260],"weighted":[263],"Baseline.":[264],"These":[265],"demonstrate":[267],"strategy":[272],"enhances":[273],"ranking":[274],"performance":[275],"minority-detection":[277],"rates,":[278],"particularly":[279],"scenarios":[281],"critical.":[285],"The":[286],"complete":[287],"implementation,":[288],"including":[289],"preprocessing,":[291],"training,":[293],"oversampling,":[295],"visualization":[299],"scripts,":[300],"at":[304],"https://github.com/yasserramadan202025/gan_smote":[305],"full":[308],"reproducibility":[309],"facilitate":[311],"further":[312],"research.":[313]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2026-04-03T00:00:00"}