{"id":"https://openalex.org/W4404351449","doi":"https://doi.org/10.1145/3677052.3698658","title":"FraudDiffuse: Diffusion-aided Synthetic Fraud Augmentation for Improved Fraud Detection","display_name":"FraudDiffuse: Diffusion-aided Synthetic Fraud Augmentation for Improved Fraud Detection","publication_year":2024,"publication_date":"2024-11-14","ids":{"openalex":"https://openalex.org/W4404351449","doi":"https://doi.org/10.1145/3677052.3698658"},"language":"en","primary_location":{"id":"doi:10.1145/3677052.3698658","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3677052.3698658","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3677052.3698658","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th ACM International Conference on AI in Finance","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3677052.3698658","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ruma Roy","orcid":"https://orcid.org/0009-0001-6055-7439"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ruma Roy","raw_affiliation_strings":["Mastercard, India"],"raw_orcid":"https://orcid.org/0009-0001-6055-7439","affiliations":[{"raw_affiliation_string":"Mastercard, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113083772","display_name":"Darshika Tiwari","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Darshika Tiwari","raw_affiliation_strings":["Mastercard, India"],"raw_orcid":"https://orcid.org/0009-0007-0334-5927","affiliations":[{"raw_affiliation_string":"Mastercard, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041382029","display_name":"Anubha Pandey","orcid":"https://orcid.org/0000-0002-4695-0947"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anubha Pandey","raw_affiliation_strings":["Mastercard, India"],"raw_orcid":"https://orcid.org/0000-0002-4695-0947","affiliations":[{"raw_affiliation_string":"Mastercard, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6623,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.76144243,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"90","last_page":"98"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9509999752044678,"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/T11182","display_name":"Auction Theory and Applications","score":0.9244999885559082,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5533739924430847},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.4233376681804657},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.391367107629776}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5533739924430847},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.4233376681804657},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.391367107629776},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3677052.3698658","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3677052.3698658","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3677052.3698658","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th ACM International Conference on AI in Finance","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3677052.3698658","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3677052.3698658","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3677052.3698658","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th ACM International Conference on AI in Finance","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4404351449.pdf","grobid_xml":"https://content.openalex.org/works/W4404351449.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W1996523702","https://openalex.org/W2295598076","https://openalex.org/W2779931100","https://openalex.org/W2945876440","https://openalex.org/W2966109816","https://openalex.org/W4306935405","https://openalex.org/W4321485139","https://openalex.org/W4321592872","https://openalex.org/W4382469817","https://openalex.org/W4388994349","https://openalex.org/W4390886362","https://openalex.org/W4394729879"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Payment":[0],"fraud":[1,27,31,114,171,184],"poses":[2],"a":[3,88,158],"severe":[4],"financial":[5],"threat,":[6],"with":[7,25,182],"staggering":[8],"global":[9],"losses.":[10],"Rapidly":[11],"evolving":[12],"fraudulent":[13,37,151,195],"patterns":[14,115,185],"challenge":[15],"machine":[16],"learning":[17,30,160],"models,":[18],"compounded":[19],"by":[20,52,116],"highly":[21],"imbalanced":[22],"training":[23,76,95,180],"datasets":[24],"few":[26],"samples.":[28,172],"Consequently,":[29],"pattern\u2019s":[32],"distribution":[33,119],"and":[34,78,96,133,169,196,221],"generating":[35,112],"synthetic":[36,113,168],"transactions":[38],"is":[39,205],"imperative.":[40],"Traditional":[41],"oversampling":[42,215],"techniques":[43,110],"like":[44,65],"SMOTE":[45],"(Synthetic":[46],"Minority":[47],"Over-sampling":[48],"Technique)":[49],"are":[50],"limited":[51],"linear":[53],"interpolation,":[54],"failing":[55],"to":[56,99,137,192],"capture":[57],"complex":[58],"data":[59,102,181],"manifolds.":[60],"While":[61],"deep":[62],"generative":[63,90],"models":[64,84],"GANs":[66],"(Generative":[67],"Adversarial":[68],"Networks)":[69],"have":[70,85],"been":[71],"explored,":[72],"they":[73],"suffer":[74],"from":[75,152],"instability":[77],"mode":[79],"collapse.":[80],"Recently,":[81],"denoising":[82],"diffusion":[83,109,223],"emerged":[86],"as":[87,123,218],"leading":[89],"modeling":[91],"paradigm,":[92],"offering":[93],"stable":[94],"the":[97,118,124,127,138,146,179,189],"ability":[98,191],"learn":[100,130],"underlying":[101],"manifolds":[103],"comprehensively.":[104],"This":[105,142,173],"paper":[106],"extends":[107],"existing":[108],"for":[111],"utilizing":[117],"of":[120,201],"non-fraudulent":[121,153,197],"samples":[122,135],"prior,":[125],"ensuring":[126],"model":[128],"can":[129],"intricate":[131],"distributions":[132],"generate":[134],"close":[136],"class":[139],"decision":[140],"boundary.":[141],"helps":[143],"in":[144],"capturing":[145],"subtle":[147],"nuances":[148],"that":[149],"distinguish":[150,193],"instances.":[154],"Furthermore,":[155],"we":[156],"integrate":[157],"contrastive":[159],"loss":[161],"function,":[162],"which":[163],"promotes":[164],"high":[165],"similarity":[166],"between":[167,194],"real":[170],"innovative":[174],"approach":[175],"not":[176],"only":[177],"enriches":[178],"realistic":[183],"but":[186],"also":[187],"strengthens":[188],"model\u2019s":[190],"transactions.":[198],"The":[199],"effectiveness":[200],"our":[202],"proposed":[203],"algorithm":[204],"validated":[206],"through":[207],"extensive":[208],"experiments,":[209],"demonstrating":[210],"its":[211],"superiority":[212],"over":[213],"traditional":[214],"methods":[216],"such":[217],"SMOTE,":[219],"GANs,":[220],"vanilla":[222],"models.":[224]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
