{"id":"https://openalex.org/W4402353589","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650265","title":"Simultaneously Detecting Node and Edge Level Anomalies on Heterogeneous Attributed Graphs","display_name":"Simultaneously Detecting Node and Edge Level Anomalies on Heterogeneous Attributed Graphs","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402353589","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650265"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650265","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650265","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5005784479","display_name":"Rizal Fathony","orcid":"https://orcid.org/0000-0003-1538-9090"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rizal Fathony","raw_affiliation_strings":["Grab,Jakarta,Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Grab,Jakarta,Indonesia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102440282","display_name":"Jenn Ng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jenn Ng","raw_affiliation_strings":["Grab,Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Grab,Singapore","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100416039","display_name":"Jia Chen","orcid":"https://orcid.org/0009-0005-0957-1744"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia Chen","raw_affiliation_strings":["Grab,Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Grab,Singapore","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994999766349792,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994999766349792,"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":0.9987999796867371,"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"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6371544599533081},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.574187695980072},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5304849743843079},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15522673726081848},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10559684038162231}],"concepts":[{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6371544599533081},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.574187695980072},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5304849743843079},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15522673726081848},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10559684038162231},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650265","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650265","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W42722137","https://openalex.org/W105848778","https://openalex.org/W2016654142","https://openalex.org/W2034778365","https://openalex.org/W2089554624","https://openalex.org/W2110953678","https://openalex.org/W2122646361","https://openalex.org/W2296719434","https://openalex.org/W2604314403","https://openalex.org/W2755088640","https://openalex.org/W2911286998","https://openalex.org/W2965857891","https://openalex.org/W2970066309","https://openalex.org/W2970641574","https://openalex.org/W2997461192","https://openalex.org/W2998336824","https://openalex.org/W3003795821","https://openalex.org/W3004507689","https://openalex.org/W3012871709","https://openalex.org/W3015799890","https://openalex.org/W3032985650","https://openalex.org/W3034122135","https://openalex.org/W3093664513","https://openalex.org/W3103513278","https://openalex.org/W3133518153","https://openalex.org/W3151900735","https://openalex.org/W3206326321","https://openalex.org/W3206604724","https://openalex.org/W3210350882","https://openalex.org/W4205471456","https://openalex.org/W4205942400","https://openalex.org/W4207072731","https://openalex.org/W4224982001","https://openalex.org/W4285066127","https://openalex.org/W4285378361","https://openalex.org/W4293704747","https://openalex.org/W4295312788","https://openalex.org/W4311414441","https://openalex.org/W4312106615","https://openalex.org/W4367047306","https://openalex.org/W4379927591","https://openalex.org/W4382202833","https://openalex.org/W4382239148","https://openalex.org/W4385488626","https://openalex.org/W4386973209","https://openalex.org/W4387185386","https://openalex.org/W4390601379","https://openalex.org/W4391549727","https://openalex.org/W4393159601","https://openalex.org/W6744271739","https://openalex.org/W6760045743","https://openalex.org/W6766978945","https://openalex.org/W6767098714","https://openalex.org/W6791639162","https://openalex.org/W6800720063","https://openalex.org/W6810969505","https://openalex.org/W6846687627","https://openalex.org/W6860096264"],"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/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"In":[0,38],"complex":[1],"systems":[2],"like":[3,97,109],"social":[4],"media":[5],"and":[6,35,56,123,158,172,195],"financial":[7],"transactions,":[8],"diverse":[9],"entities":[10,171],"(users,":[11],"groups,":[12],"products)":[13],"interact":[14],"through":[15],"a":[16,80,146,179,185],"multitude":[17],"of":[18,131,136,154,181,193],"relationships":[19],"(friendships,":[20],"comments,":[21],"purchases).":[22],"These":[23],"interactions":[24],"can":[25],"be":[26],"represented":[27],"by":[28,164],"heterogeneous":[29,137,162],"graphs":[30,43,63,122],"(graphs":[31],"with":[32,184],"many":[33,39],"node":[34],"edge":[36],"types).":[37],"real-world":[40,211],"applications,":[41],"these":[42,62],"may":[44,69,75,93],"contain":[45],"unusual":[46,95],"patterns":[47],"or":[48,103],"anomalies.":[49],"Detecting":[50],"anomalies,":[51,60],"both":[52],"entity":[53],"(node)":[54],"level":[55,59],"interaction":[57,101],"(edge)":[58],"in":[61,100,169,209,221],"are":[64],"important,":[65],"as":[66,84,178],"their":[67],"occurrence":[68],"have":[70],"serious":[71],"implications.":[72],"Node-level":[73],"anomalies":[74,92,160,197],"indicate":[76],"abnormal":[77],"behavior":[78],"from":[79],"specific":[81],"entity,":[82],"such":[83],"unexpected":[85,98],"activity":[86],"that":[87,152],"could":[88],"suggest":[89],"fraud.":[90],"Edge-level":[91],"signify":[94],"interactions,":[96],"changes":[99],"frequency":[102],"pattern,":[104],"potentially":[105],"indicating":[106],"collaborative":[107],"fraud":[108],"collusion.Unfortunately,":[110],"existing":[111],"graph":[112,138,148,182,200],"neural":[113,149,201],"network":[114,150,202],"anomaly":[115,218],"detection":[116,192,219],"models":[117],"focus":[118],"only":[119,125],"on":[120,161],"homogeneous":[121],"consider":[124],"node-level":[126,157,194],"detection,":[127],"rendering":[128],"them":[129],"incapable":[130],"harnessing":[132,165],"the":[133,166,170,191,222],"full":[134],"complexity":[135],"data.":[139],"To":[140],"address":[141],"this":[142],"limitation,":[143],"we":[144],"present":[145],"new":[147],"model":[151,177],"capable":[153],"simultaneously":[155],"detecting":[156],"edge-level":[159,196],"graphs,":[163],"rich":[167],"information":[168],"relations.":[173],"We":[174],"develop":[175],"our":[176,214],"type":[180],"autoencoder":[183],"customized":[186],"architecture":[187],"design":[188],"to":[189],"enable":[190],"simultaneously.":[198],"Our":[199],"structure":[203],"is":[204],"scalable,":[205],"facilitating":[206],"its":[207],"application":[208],"large":[210],"scenarios.":[212],"Finally,":[213],"method":[215],"outperforms":[216],"previous":[217],"methods":[220],"experiments.":[223]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
