{"id":"https://openalex.org/W4392024995","doi":"https://doi.org/10.1109/tifs.2024.3368879","title":"RVE-PFL: Robust Variational Encoder-Based Personalized Federated Learning Against Model Inversion Attacks","display_name":"RVE-PFL: Robust Variational Encoder-Based Personalized Federated Learning Against Model Inversion Attacks","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4392024995","doi":"https://doi.org/10.1109/tifs.2024.3368879"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2024.3368879","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2024.3368879","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Information Forensics and Security","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/A5022404407","display_name":"Wael Issa","orcid":"https://orcid.org/0000-0002-4366-1373"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]},{"id":"https://openalex.org/I40053085","display_name":"Australian Defence Force Academy","ror":"https://ror.org/02j5s7g39","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571","https://openalex.org/I40053085","https://openalex.org/I4394709116"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Wael Issa","raw_affiliation_strings":["ADFA, University of New South Wales, Canberra, ACT, Australia"],"raw_orcid":"https://orcid.org/0000-0002-4366-1373","affiliations":[{"raw_affiliation_string":"ADFA, University of New South Wales, Canberra, ACT, Australia","institution_ids":["https://openalex.org/I31746571","https://openalex.org/I40053085"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089327837","display_name":"Nour Moustafa","orcid":"https://orcid.org/0000-0001-6127-9349"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]},{"id":"https://openalex.org/I40053085","display_name":"Australian Defence Force Academy","ror":"https://ror.org/02j5s7g39","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571","https://openalex.org/I40053085","https://openalex.org/I4394709116"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Nour Moustafa","raw_affiliation_strings":["ADFA, University of New South Wales, Canberra, ACT, Australia"],"raw_orcid":"https://orcid.org/0000-0001-6127-9349","affiliations":[{"raw_affiliation_string":"ADFA, University of New South Wales, Canberra, ACT, Australia","institution_ids":["https://openalex.org/I31746571","https://openalex.org/I40053085"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022626159","display_name":"Benjamin Turnbull","orcid":"https://orcid.org/0000-0003-0440-5032"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Benjamin Turnbull","raw_affiliation_strings":["Australian Centre for Cyber Security, University of New South Wales, Campbell, ACT, Australia"],"raw_orcid":"https://orcid.org/0000-0003-0440-5032","affiliations":[{"raw_affiliation_string":"Australian Centre for Cyber Security, University of New South Wales, Campbell, ACT, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001746807","display_name":"Kim\u2010Kwang Raymond Choo","orcid":"https://orcid.org/0000-0001-9208-5336"},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kim-Kwang Raymond Choo","raw_affiliation_strings":["Department of Information Systems and Cyber Security, The University of Texas at San Antonio, San Antonio, TX, USA"],"raw_orcid":"https://orcid.org/0000-0001-9208-5336","affiliations":[{"raw_affiliation_string":"Department of Information Systems and Cyber Security, The University of Texas at San Antonio, San Antonio, TX, USA","institution_ids":["https://openalex.org/I45438204"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.011,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.9664431,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"19","issue":null,"first_page":"3772","last_page":"3787"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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":1.0,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9926000237464905,"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/T10237","display_name":"Cryptography and Data Security","score":0.9632999897003174,"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":0.8383625745773315},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6221553683280945},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.604084849357605},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.575810968875885},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40304452180862427},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.33054104447364807},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.07536795735359192}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8383625745773315},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6221553683280945},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.604084849357605},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.575810968875885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40304452180862427},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.33054104447364807},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.07536795735359192},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2024.3368879","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2024.3368879","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W2051267297","https://openalex.org/W2473418344","https://openalex.org/W2789304371","https://openalex.org/W2948978827","https://openalex.org/W2955806548","https://openalex.org/W2970606380","https://openalex.org/W2976621868","https://openalex.org/W2984242138","https://openalex.org/W2989885118","https://openalex.org/W2990239018","https://openalex.org/W2993463367","https://openalex.org/W3000479830","https://openalex.org/W3003276190","https://openalex.org/W3016632787","https://openalex.org/W3023243379","https://openalex.org/W3084432478","https://openalex.org/W3111919937","https://openalex.org/W3114953370","https://openalex.org/W3133814152","https://openalex.org/W3135347465","https://openalex.org/W3153872861","https://openalex.org/W3155912831","https://openalex.org/W3159080474","https://openalex.org/W3172836181","https://openalex.org/W3200945864","https://openalex.org/W3203780767","https://openalex.org/W3209696639","https://openalex.org/W3209752568","https://openalex.org/W3210103168","https://openalex.org/W3215939271","https://openalex.org/W4220883012","https://openalex.org/W4223957328","https://openalex.org/W4287906413","https://openalex.org/W4310141801","https://openalex.org/W4312815981","https://openalex.org/W4313459321","https://openalex.org/W4315629571","https://openalex.org/W4375798903","https://openalex.org/W6728757088","https://openalex.org/W6764838729","https://openalex.org/W6772318479","https://openalex.org/W6773039429","https://openalex.org/W6780438843","https://openalex.org/W6784037095","https://openalex.org/W6789723219","https://openalex.org/W6803951002","https://openalex.org/W6805407591","https://openalex.org/W6810249531","https://openalex.org/W7016021835"],"related_works":["https://openalex.org/W4298221930","https://openalex.org/W2777914285","https://openalex.org/W3013363440","https://openalex.org/W4287823391","https://openalex.org/W4390516098","https://openalex.org/W2181948922","https://openalex.org/W4312762663","https://openalex.org/W2384362569","https://openalex.org/W2142795561","https://openalex.org/W4317941881"],"abstract_inverted_index":{"Federated":[0],"learning":[1,9],"(FL)":[2],"enables":[3],"distributed":[4],"joint":[5],"training":[6],"of":[7,186,202],"machine":[8],"(ML)":[10],"models":[11],"without":[12],"the":[13,50,121,127,200,211],"need":[14],"to":[15,24,45,60,101],"share":[16],"local":[17],"data.":[18],"FL":[19,35,72,99,180],"is,":[20],"however,":[21],"not":[22],"immune":[23],"privacy":[25],"threats":[26],"such":[27],"as":[28],"model":[29,80],"inversion":[30],"(MI)":[31],"attacks.":[32,109],"The":[33,110,157,214],"conventional":[34],"paradigm":[36],"often":[37],"uses":[38],"privacy-preserving":[39],"techniques,":[40],"and":[41,53,82,94,106,130,141,155,170,189,194],"this":[42,62,64],"could":[43],"lead":[44],"a":[46,67,95],"considerable":[47],"loss":[48],"in":[49,143,204],"model\u2019s":[51,212],"utility":[52],"consequently":[54],"compromised":[55],"by":[56],"MI":[57,77,108,207],"attackers.":[58],"Seeking":[59],"address":[61],"limitation,":[63],"paper":[65],"proposes":[66],"robust":[68],"variational":[69,91],"encoder-based":[70],"personalised":[71,90],"(RVE-PFL)":[73],"approach":[74,123],"that":[75,161],"mitigates":[76],"attacks,":[78],"preserves":[79],"utility,":[81],"ensures":[83],"data":[84,104,116,125,169],"privacy.":[85],"RVE-PFL":[86,145,162,203,218],"comprises":[87],"an":[88],"innovative":[89],"encoder":[92],"architecture":[93,112],"trustworthy":[96],"threat":[97],"model-integrated":[98],"method":[100],"autonomously":[102],"preserve":[103],"privacy,":[105],"mitigate":[107],"proposed":[111,122],"seamlessly":[113],"trains":[114],"heterogeneous":[115],"at":[117,126],"every":[118],"client,":[119],"while":[120,167,209],"aggregates":[124],"server":[128],"side":[129],"effectively":[131],"discriminates":[132],"against":[133,206],"adversarial":[134,172],"settings":[135],"(i.e.,":[136],"MI);":[137],"thus,":[138],"achieving":[139],"robustness":[140],"trustworthiness":[142],"real-time.":[144],"is":[146],"evaluated":[147],"on":[148,191,222],"three":[149],"benchmark":[150],"datasets,":[151],"namely:":[152],"MNIST,":[153,192],"Fashion-MNIST,":[154,193],"Cifar-10.":[156],"experimental":[158],"results":[159],"revealed":[160],"achieves":[163],"high":[164],"accuracy":[165,184],"level":[166],"preserving":[168],"tuning":[171],"settings.":[173],"It":[174],"outperforms":[175],"Noising":[176],"before":[177],"Model":[178],"Aggregation":[179],"(NbAFL)":[181],"with":[182],"significant":[183],"improvements":[185],"8%,":[187],"20%,":[188],"59%":[190],"Cifar-10,":[195],"respectively.":[196],"These":[197],"findings":[198],"reinforce":[199],"effectiveness":[201],"protecting":[205],"attacks":[208],"maintaining":[210],"utility.":[213],"source":[215],"code":[216],"for":[217],"can":[219],"be":[220],"found":[221],"GitHub":[223],"1.":[224]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":5}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}