{"id":"https://openalex.org/W4403708933","doi":"https://doi.org/10.1145/3690407.3690589","title":"NMFA: Node-Level Multi-Frequency Adaptive Graph Neural Network for Graph Fraud Detection","display_name":"NMFA: Node-Level Multi-Frequency Adaptive Graph Neural Network for Graph Fraud Detection","publication_year":2024,"publication_date":"2024-06-21","ids":{"openalex":"https://openalex.org/W4403708933","doi":"https://doi.org/10.1145/3690407.3690589"},"language":"en","primary_location":{"id":"doi:10.1145/3690407.3690589","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3690407.3690589","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 4th International Conference on Artificial Intelligence, Big Data and Algorithms","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114388115","display_name":"Pin Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I137056471","display_name":"Nanjing University of Finance and Economics","ror":"https://ror.org/031y8am81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137056471"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pin Xu","raw_affiliation_strings":["School of Information Engineering, Nanjing University of Finance and Economics, Nanjing, Jiangsu, China"],"raw_orcid":"https://orcid.org/0009-0004-2245-0771","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Nanjing University of Finance and Economics, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I137056471"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070846571","display_name":"Youquan Wang","orcid":"https://orcid.org/0000-0003-4726-7493"},"institutions":[{"id":"https://openalex.org/I137056471","display_name":"Nanjing University of Finance and Economics","ror":"https://ror.org/031y8am81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137056471"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youquan Wang","raw_affiliation_strings":["Jiangsu Provincial Key Laboratory of E-Business, Nanjing University of Finance and Economics, Nanjing, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0003-4726-7493","affiliations":[{"raw_affiliation_string":"Jiangsu Provincial Key Laboratory of E-Business, Nanjing University of Finance and Economics, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I137056471"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mingjie Wu","orcid":"https://orcid.org/0009-0001-2960-8234"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingjie Wu","raw_affiliation_strings":["School of Management, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, China"],"raw_orcid":"https://orcid.org/0009-0001-2960-8234","affiliations":[{"raw_affiliation_string":"School of Management, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zixu Gao","orcid":"https://orcid.org/0009-0006-1329-5620"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zixu Gao","raw_affiliation_strings":["School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, Jiangsu, China"],"raw_orcid":"https://orcid.org/0009-0006-1329-5620","affiliations":[{"raw_affiliation_string":"School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I200845125"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5114388115"],"corresponding_institution_ids":["https://openalex.org/I137056471"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16154832,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1094","last_page":"1100"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9977999925613403,"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":0.9977999925613403,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9944999814033508,"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/computer-science","display_name":"Computer science","score":0.7273409962654114},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5408186912536621},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44581109285354614},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3003309965133667},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22262486815452576}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7273409962654114},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5408186912536621},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44581109285354614},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3003309965133667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22262486815452576}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3690407.3690589","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3690407.3690589","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 4th International Conference on Artificial Intelligence, Big Data and Algorithms","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6700000166893005,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2064058256","https://openalex.org/W2136891251","https://openalex.org/W2519887557","https://openalex.org/W2624431344","https://openalex.org/W2971933740","https://openalex.org/W3016757214","https://openalex.org/W3068123808","https://openalex.org/W3095521706","https://openalex.org/W3099825604","https://openalex.org/W3102969158","https://openalex.org/W3120106766","https://openalex.org/W3128443161","https://openalex.org/W3153858161","https://openalex.org/W4224310669","https://openalex.org/W4280545892","https://openalex.org/W4281655877","https://openalex.org/W4297347671","https://openalex.org/W4321276816","https://openalex.org/W4367047347"],"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":{"Fraudsters":[0],"excel":[1],"at":[2,121],"concealing":[3],"themselves":[4],"by":[5],"establishing":[6],"connections":[7],"with":[8,113],"many":[9,74],"trustworthy":[10],"users":[11],"to":[12,50,69,164],"evade":[13],"detectors.":[14],"This":[15],"cunning":[16],"behavior":[17],"increases":[18],"the":[19,22,62,66,81,140,165],"heterogeneity":[20],"within":[21],"graph,":[23,63],"rendering":[24],"ineffective":[25],"Graph":[26,104],"Neural":[27,105],"Network":[28,106],"(GNN)":[29],"methods":[30,48,75],"based":[31,138],"on":[32,139,151],"homogeneity":[33],"assumptions.":[34],"To":[35,91],"tackle":[36],"this":[37],"problem,":[38],"several":[39],"spectral":[40],"GNN-based":[41],"approaches":[42],"have":[43],"been":[44],"introduced.":[45],"However,":[46],"existing":[47],"fail":[49],"fully":[51],"exploit":[52],"frequency":[53,124],"information,":[54],"often":[55],"overlooking":[56],"signals":[57],"of":[58,84],"other":[59],"frequencies":[60,83],"in":[61],"which":[64],"diminishes":[65],"model's":[67],"ability":[68],"capture":[70],"node":[71,127],"characteristics.":[72],"Furthermore,":[73],"employ":[76],"global":[77],"filtering":[78,145],"GNNs,":[79],"neglecting":[80],"different":[82],"attention":[85,141],"for":[86,126,146],"fraudulent":[87],"and":[88,119],"benign":[89],"nodes.":[90],"mitigate":[92],"these":[93],"shortcomings,":[94],"we":[95,131],"propose":[96],"a":[97,133],"new":[98],"method":[99,110,157],"called":[100],"Node-Level":[101],"Multi-Frequency":[102],"Adaptive":[103],"(NMFA).":[107],"Specifically,":[108],"our":[109,156],"is":[111],"equipped":[112],"three":[114],"multi-frequency":[115,134],"filter":[116],"groups\u2014low-pass,":[117],"band-pass,":[118],"high-pass\u2014aimed":[120],"extracting":[122],"comprehensive":[123],"information":[125],"representation":[128],"learning.":[129],"Moreover,":[130],"devised":[132],"adaptive":[135],"fusion":[136],"mechanism":[137],"mechanism,":[142],"enabling":[143],"personalized":[144],"each":[147],"node.":[148],"Experiments":[149],"conducted":[150],"real":[152],"datasets":[153],"demonstrate":[154],"that":[155],"significantly":[158],"improves":[159],"fraud":[160,168],"detection":[161,169],"performance":[162],"compared":[163],"advanced":[166],"GNN":[167],"methods.":[170]},"counts_by_year":[],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}