{"id":"https://openalex.org/W2896916493","doi":"https://doi.org/10.1109/tkde.2018.2876531","title":"A Contrast Metric for Fraud Detection in Rich Graphs","display_name":"A Contrast Metric for Fraud Detection in Rich Graphs","publication_year":2018,"publication_date":"2018-10-17","ids":{"openalex":"https://openalex.org/W2896916493","doi":"https://doi.org/10.1109/tkde.2018.2876531","mag":"2896916493"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2018.2876531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2018.2876531","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5100677836","display_name":"Shenghua Liu","orcid":"https://orcid.org/0000-0003-2120-3598"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Shenghua Liu","raw_affiliation_strings":["CAS Key Laboratory of Network Data Science & Technology, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","Carnegie Mellon University, Pittsburgh, USA"],"raw_orcid":"https://orcid.org/0000-0003-2120-3598","affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Network Data Science & Technology, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065675832","display_name":"Bryan Hooi","orcid":"https://orcid.org/0000-0002-5645-1754"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bryan Hooi","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, USA"],"raw_orcid":"https://orcid.org/0000-0002-5645-1754","affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035605036","display_name":"Christos Faloutsos","orcid":"https://orcid.org/0000-0003-2996-9790"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christos Faloutsos","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.305,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.96749287,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"31","issue":"12","first_page":"2235","last_page":"2248"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9998999834060669,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9879000186920166,"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":0.9872999787330627,"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":0.747753381729126},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.6305254101753235},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5671030879020691},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2683206796646118}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.747753381729126},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.6305254101753235},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5671030879020691},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2683206796646118},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2018.2876531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2018.2876531","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.8100000023841858}],"awards":[{"id":"https://openalex.org/G6975804268","display_name":"\u5927\u89c4\u6a21\u591a\u5c5e\u6027\u56fe\u4e2d\u7684\u5f02\u5e38\u6a21\u5f0f\u6316\u6398","funder_award_id":"61772498","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8474963640","display_name":"\u9762\u5411\u5927\u6570\u636e\u667a\u80fd\u5904\u7406\u7684\u968f\u673a\u77e9\u9635\u4e0e\u5f20\u91cf\u7b97\u6cd5\u7814\u7a76","funder_award_id":"61872206","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G948678646","display_name":null,"funder_award_id":"W911NF-09-2-0053","funder_id":"https://openalex.org/F4320338295","funder_display_name":"Army Research Laboratory"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W81017276","https://openalex.org/W746997338","https://openalex.org/W1492581097","https://openalex.org/W1535144194","https://openalex.org/W1560607100","https://openalex.org/W1604983895","https://openalex.org/W1947476231","https://openalex.org/W2020214545","https://openalex.org/W2024932032","https://openalex.org/W2048092465","https://openalex.org/W2054526494","https://openalex.org/W2061873838","https://openalex.org/W2085573882","https://openalex.org/W2101447063","https://openalex.org/W2103063352","https://openalex.org/W2107884625","https://openalex.org/W2111639622","https://openalex.org/W2112056172","https://openalex.org/W2133591726","https://openalex.org/W2133777675","https://openalex.org/W2136690843","https://openalex.org/W2136710010","https://openalex.org/W2136891251","https://openalex.org/W2144211451","https://openalex.org/W2148123869","https://openalex.org/W2148972377","https://openalex.org/W2150739536","https://openalex.org/W2171817276","https://openalex.org/W2189187207","https://openalex.org/W2248736178","https://openalex.org/W2282288858","https://openalex.org/W2293768274","https://openalex.org/W2337240321","https://openalex.org/W2348679751","https://openalex.org/W2473813716","https://openalex.org/W2513234781","https://openalex.org/W2562676961","https://openalex.org/W2584910459","https://openalex.org/W2586047314","https://openalex.org/W2604992511","https://openalex.org/W2613993493","https://openalex.org/W2730363704","https://openalex.org/W2902455138","https://openalex.org/W2962752671","https://openalex.org/W3003141074","https://openalex.org/W3101251439","https://openalex.org/W4238201623","https://openalex.org/W4293355737","https://openalex.org/W6629457467","https://openalex.org/W6633459302","https://openalex.org/W6636143309","https://openalex.org/W6662878164","https://openalex.org/W6684043126","https://openalex.org/W6687142891","https://openalex.org/W6695774259","https://openalex.org/W6756753118"],"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":{"How":[0],"can":[1],"we":[2,78,139],"detect":[3,98],"fraud":[4,196],"in":[5,45,68],"a":[6,83,162],"big":[7],"graph":[8,91],"with":[9,186,194],"rich":[10],"properties,":[11],"as":[12,42,50],"online":[13],"fraudsters":[14,111,126,154],"invest":[15],"more":[16,63,96],"resources,":[17],"including":[18,62],"purchasing":[19],"large":[20],"pools":[21],"of":[22,61,118,125,129],"fake":[23],"user":[24],"accounts":[25],"and":[26,71,93,101,112,122,132,134,165,173,189],"dedicated":[27],"IPs,":[28],"to":[29,95,155],"hide":[30],"their":[31],"fraudulent":[32,99],"attacks?":[33],"To":[34],"achieve":[35],"robustness,":[36],"existing":[37],"approaches":[38,56],"detected":[39],"dense":[40],"sub-graphs":[41],"suspicious":[43],"patterns":[44,109],"an":[46],"unsupervised":[47],"way,":[48],"such":[49,55],"average":[51],"degree":[52],"maximization.":[53],"However,":[54],"suffer":[57],"from":[58,90],"the":[59,107,120,149,170],"bias":[60],"nodes":[64],"than":[65],"necessary,":[66],"resulting":[67],"lower":[69],"accuracy":[70,181],"increased":[72],"need":[73],"for":[74,143,153],"manual":[75],"verification.":[76],"Therefore,":[77],"propose":[79],"HoloScope,":[80],"which":[81],"introduces":[82],"novel":[84],"metric":[85],"\u201ccontrast":[86],"suspiciousness\u201d":[87],"integrating":[88],"information":[89],"topology":[92],"spikes":[94],"accurately":[97],"users":[100],"objects.":[102],"Contrast":[103],"suspiciousness":[104],"dynamically":[105],"emphasizes":[106],"contrasting":[108],"between":[110],"normal":[113],"users,":[114],"making":[115,169],"HoloScope":[116,160,178],"capable":[117],"distinguishing":[119],"synchronized":[121],"strange":[123],"behaviors":[124],"by":[127],"means":[128],"topology,":[130],"bursts":[131],"drops,":[133],"rating":[135],"scores.":[136],"In":[137,175],"addition,":[138],"provide":[140],"theoretical":[141],"bounds":[142],"how":[144],"much":[145],"this":[146],"method":[147],"increases":[148],"time":[150,167],"cost":[151],"needed":[152],"conduct":[156],"adversarial":[157],"attacks.":[158],"Moreover,":[159],"has":[161],"concise":[163],"framework":[164],"sub-quadratic":[166],"complexity,":[168],"algorithm":[171],"reproducible":[172],"scalable.":[174],"extensive":[176],"experiments,":[177],"achieved":[179],"significant":[180],"improvements":[182],"on":[183],"real":[184],"data":[185],"injected":[187],"labels":[188],"true":[190],"labels,":[191],"when":[192],"compared":[193],"state-of-the-art":[195],"detection":[197],"methods.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}