{"id":"https://openalex.org/W7135226767","doi":"https://doi.org/10.1109/ojcoms.2026.3673841","title":"TMRGNN: Temporal Multi-Relation Graph Neural Network for Malicious Client Detection in Federated Learning","display_name":"TMRGNN: Temporal Multi-Relation Graph Neural Network for Malicious Client Detection in Federated Learning","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7135226767","doi":"https://doi.org/10.1109/ojcoms.2026.3673841"},"language":"en","primary_location":{"id":"doi:10.1109/ojcoms.2026.3673841","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcoms.2026.3673841","pdf_url":null,"source":{"id":"https://openalex.org/S4210202420","display_name":"IEEE Open Journal of the Communications Society","issn_l":"2644-125X","issn":["2644-125X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Open Journal of the Communications Society","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/ojcoms.2026.3673841","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120627798","display_name":"Anuja Kunjumon","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anuja Kunjumon","raw_affiliation_strings":["Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, India"],"raw_orcid":"https://orcid.org/0009-0009-7700-6762","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128923547","display_name":"E V Sunitha","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"E. V. Sunitha","raw_affiliation_strings":["Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, India"],"raw_orcid":"https://orcid.org/0000-0003-4447-3216","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041549614","display_name":"Jyothisha J. Nair","orcid":"https://orcid.org/0000-0002-8050-8896"},"institutions":[{"id":"https://openalex.org/I177436651","display_name":"Mahatma Gandhi University","ror":"https://ror.org/00h4spn88","country_code":"IN","type":"education","lineage":["https://openalex.org/I177436651"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jyothisha J. Nair","raw_affiliation_strings":["School of Computer Sciences, Mahatma Gandhi University, Kottayam, Kerala, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Sciences, Mahatma Gandhi University, Kottayam, Kerala, India","institution_ids":["https://openalex.org/I177436651"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1750,"currency":"USD","value_usd":1750},"apc_paid":{"value":1750,"currency":"USD","value_usd":1750},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33997631,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":null,"first_page":"2588","last_page":"2606"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.22339999675750732,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.22339999675750732,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.07599999755620956,"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":0.06520000100135803,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4927000105381012},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4189000129699707},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.36809998750686646},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2913999855518341},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.28349998593330383},{"id":"https://openalex.org/keywords/distributed-learning","display_name":"Distributed learning","score":0.27790001034736633}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7556999921798706},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4927000105381012},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4368000030517578},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4189000129699707},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.36809998750686646},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.36079999804496765},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33009999990463257},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26579999923706055},{"id":"https://openalex.org/C152880691","wikidata":"https://www.wikidata.org/wiki/Q146813","display_name":"Client\u2013server model","level":3,"score":0.2632000148296356},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2542000114917755}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ojcoms.2026.3673841","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcoms.2026.3673841","pdf_url":null,"source":{"id":"https://openalex.org/S4210202420","display_name":"IEEE Open Journal of the Communications Society","issn_l":"2644-125X","issn":["2644-125X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Open Journal of the Communications Society","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:131b7f8c801e438086c796c83aaacccb","is_oa":true,"landing_page_url":"https://doaj.org/article/131b7f8c801e438086c796c83aaacccb","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Open Journal of the Communications Society, Vol 7, Pp 2588-2606 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/ojcoms.2026.3673841","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcoms.2026.3673841","pdf_url":null,"source":{"id":"https://openalex.org/S4210202420","display_name":"IEEE Open Journal of the Communications Society","issn_l":"2644-125X","issn":["2644-125X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Open Journal of the Communications Society","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Federated":[0],"learning":[1,189,200],"remains":[2],"inherently":[3],"vulnerable":[4],"in":[5,140,178],"practical":[6],"deployments,":[7],"as":[8,69],"malicious":[9],"clients":[10,142,152],"can":[11,143],"behave":[12],"unpredictably,":[13],"launch":[14],"coordinated":[15],"delayed":[16,138],"attacks,":[17,159],"and":[18,83,85,108,122,134],"exploit":[19],"non-IID":[20,123],"data":[21],"heterogeneity":[22],"to":[23,90,166],"obscure":[24],"their":[25],"adversarial":[26,115,164],"behavior.":[27],"Existing":[28],"defenses,":[29],"including":[30],"those":[31],"adopted":[32],"by":[33],"federated":[34,199],"learning,":[35],"fail":[36],"because":[37],"they":[38],"rely":[39],"on":[40,120],"single-round":[41],"or":[42,53],"single-view":[43],"heuristics,":[44],"which":[45,141,171],"inevitably":[46],"break":[47],"down":[48],"when":[49,149],"faced":[50],"with":[51,168],"temporal":[52,72,99,186],"statistical":[54],"shifts.":[55],"We":[56],"present":[57],"TMRGNN,":[58],"a":[59,70,109,191],"Temporal":[60],"Multi-Relation":[61],"Graph":[62],"Neural":[63],"Network":[64],"that":[65,185],"reimagines":[66],"FL":[67],"security":[68],"multi-view":[71],"reasoning":[73],"problem.":[74],"TMRGNN":[75,126,155],"constructs":[76],"four":[77],"complementing":[78],"relational":[79],"graphs\u2014parameter,":[80],"gradient,":[81],"prediction,":[82],"communication":[84],"subsequently":[86],"utilizes":[87],"graph":[88,188],"attention":[89],"differentiate":[91],"small":[92],"adversary":[93],"signals":[94],"from":[95],"benign":[96],"heterogeneity.":[97],"A":[98],"feature":[100],"engine":[101],"captures":[102],"changing":[103],"behavioral":[104],"dynamics":[105],"over":[106,146],"time,":[107,147],"GRU-based":[110],"fusion":[111],"layer":[112],"tracks":[113],"long-range":[114],"drift.":[116],"In":[117],"extensive":[118],"experiments":[119],"IID":[121],"task":[124],"distributions,":[125],"achieves":[127],"100%":[128],"recall":[129,136],"for":[130,195],"all":[131],"early-stage":[132],"attacks":[133,139,145],"0.91-0.97":[135],"under":[137],"coordinate":[144],"even":[148],"30%":[150],"of":[151],"are":[153],"malicious.":[154],"also":[156],"identifies":[157],"slow-drift":[158],"among":[160],"the":[161,179],"most":[162],"difficult":[163],"strategies":[165],"detect,":[167],"0.85-0.90":[169],"recall,":[170],"is":[172,190],"well":[173],"above":[174],"existing":[175],"defenses":[176],"capabilities":[177],"same":[180],"setting.":[181],"Our":[182],"work":[183],"demonstrates":[184],"multi-relation":[187],"highly":[192],"effective":[193],"paradigm":[194],"securing":[196],"next":[197],"generation":[198],"systems.":[201]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-14T00:00:00"}
