{"id":"https://openalex.org/W4388994510","doi":"https://doi.org/10.1145/3604237.3626890","title":"Improving the Robustness of Financial Models through Identification of the Minimal Vulnerable Feature Set","display_name":"Improving the Robustness of Financial Models through Identification of the Minimal Vulnerable Feature Set","publication_year":2023,"publication_date":"2023-11-25","ids":{"openalex":"https://openalex.org/W4388994510","doi":"https://doi.org/10.1145/3604237.3626890"},"language":"en","primary_location":{"id":"doi:10.1145/3604237.3626890","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3604237.3626890","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3604237.3626890","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"4th ACM International Conference on AI in Finance","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3604237.3626890","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","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":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064690268","display_name":"Himanshu Chaudhary","orcid":"https://orcid.org/0009-0008-1688-5284"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Himanshu Chaudhary","raw_affiliation_strings":["University of Wisconsin, United States"],"raw_orcid":"https://orcid.org/0009-0008-1688-5284","affiliations":[{"raw_affiliation_string":"University of Wisconsin, United States","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031601018","display_name":"Alekhya Bhatraju","orcid":"https://orcid.org/0000-0003-1447-2896"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alekhya Bhatraju","raw_affiliation_strings":["Mastercard, India"],"raw_orcid":"https://orcid.org/0000-0003-1447-2896","affiliations":[{"raw_affiliation_string":"Mastercard, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103249245","display_name":"Deepak Bhatt","orcid":"https://orcid.org/0000-0003-3694-1315"},"institutions":[{"id":"https://openalex.org/I4210126839","display_name":"Mastercard (United States)","ror":"https://ror.org/043cxr310","country_code":"US","type":"company","lineage":["https://openalex.org/I4210126839"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deepak Bhatt","raw_affiliation_strings":["Mastercard, Unites States"],"raw_orcid":"https://orcid.org/0000-0003-3694-1315","affiliations":[{"raw_affiliation_string":"Mastercard, Unites States","institution_ids":["https://openalex.org/I4210126839"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084235091","display_name":"Maneet Singh","orcid":"https://orcid.org/0000-0001-5086-1026"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maneet Singh","raw_affiliation_strings":["Mastercard, India"],"raw_orcid":"https://orcid.org/0000-0001-5086-1026","affiliations":[{"raw_affiliation_string":"Mastercard, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2173,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.47798056,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"297","last_page":"304"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9986000061035156,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9986000061035156,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9959999918937683,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9750999808311462,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/robustness","display_name":"Robustness (evolution)","score":0.8151459693908691},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5427217483520508},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.46615421772003174},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42686212062835693}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8151459693908691},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5427217483520508},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.46615421772003174},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42686212062835693},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3604237.3626890","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3604237.3626890","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3604237.3626890","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"4th ACM International Conference on AI in Finance","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3604237.3626890","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3604237.3626890","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3604237.3626890","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"4th ACM International Conference on AI in Finance","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388994510.pdf","grobid_xml":"https://content.openalex.org/works/W4388994510.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W1992222410","https://openalex.org/W2180612164","https://openalex.org/W2243397390","https://openalex.org/W2295598076","https://openalex.org/W2533835508","https://openalex.org/W2747329762","https://openalex.org/W2756359217","https://openalex.org/W2963366334","https://openalex.org/W2963564844","https://openalex.org/W3015001695","https://openalex.org/W3015625436","https://openalex.org/W3096831136","https://openalex.org/W3105400121","https://openalex.org/W4231211138"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032","https://openalex.org/W2382290278"],"abstract_inverted_index":{"Research":[0],"in":[1,10,20,25,129,169,175,185,221,226],"adversarial":[2,90,228],"robustness":[3],"has":[4,113],"primarily":[5],"focused":[6],"on":[7,63,212,232],"neural":[8],"networks":[9],"domains":[11],"like":[12,188],"computer":[13],"vision,":[14],"neglecting":[15],"heterogeneous":[16,58],"tabular":[17,59],"datasets":[18],"prevalent":[19],"finance.":[21],"The":[22,138],"financial":[23],"domain,":[24],"particular,":[26],"faces":[27],"a":[28,65,104,126,167,182,200,224,239],"heightened":[29],"risk,":[30],"where":[31],"malicious":[32],"actors":[33],"may":[34],"exploit":[35],"ML":[36,244],"model":[37,210],"vulnerabilities":[38],"to":[39,52,75,85,155,166,195],"manipulate":[40],"transactions":[41],"and":[42,61,133,152,174,193],"gain":[43],"unauthorized":[44],"access.":[45],"To":[46,101],"address":[47],"this":[48,102],"gap,":[49],"we":[50],"aim":[51],"simulate":[53],"the":[54,96,109,118,134,148,153,170,189,209,213,217,227,233],"adversaries\u2019":[55],"intentions":[56],"using":[57,143,158,216],"data":[60],"focus":[62],"identifying":[64],"minimal":[66,119],"vulnerable":[67,120],"set":[68],"of":[69,98,136,150,172,191],"features":[70,81],"that":[71,208],"are":[72],"most":[73],"susceptible":[74],"an":[76],"external":[77],"attack.":[78],"Identifying":[79],"such":[80],"can":[82],"enable":[83],"developers":[84,238],"safeguard":[86],"their":[87],"models":[88],"against":[89],"attacks":[91,157],"by":[92],"updating":[93],"or":[94],"refining":[95],"rules":[97],"deployed":[99],"models.":[100,245],"effect,":[103],"GAN-based":[105],"architecture,":[106],"termed":[107],"as":[108],"Feature":[110],"Selector":[111],"Network,":[112],"been":[114],"proposed":[115,139,218],"for":[116,242],"learning":[117],"feature":[121],"set.":[122],"Experimental":[123],"evaluation":[124],"shows":[125],"significant":[127,183],"reduction":[128,168],"attack":[130,144,161,177,229],"generation":[131,178],"time":[132,154],"number":[135,149,171],"queries.":[137],"method":[140],"is":[141],"tested":[142],"imperceptibility":[145,186],"performance":[146],"metrics,":[147],"queries,":[151],"generate":[156],"existing":[159],"state-of-the-art":[160],"algorithms.":[162],"We":[163],"observed":[164],"up":[165],"queries":[173],"overall":[176],"time,":[179],"along":[180],"with":[181],"improvement":[184],"metrics":[187],"Norm":[190],"perturbations":[192],"distance":[194],"closest":[196],"neighbor":[197],"while":[198],"achieving":[199],"good":[201],"success":[202,230],"rate.":[203],"Further":[204],"experimental":[205],"analysis":[206],"suggested":[207],"trained":[211],"adversaries":[214],"generated":[215],"pipeline":[219],"resulted":[220],"more":[222],"than":[223],"decrease":[225],"rate":[231],"test":[234],"set,":[235],"thus":[236],"allowing":[237],"robust":[240],"technique":[241],"safeguarding":[243]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}