{"id":"https://openalex.org/W4396629473","doi":"https://doi.org/10.1109/tnnls.2024.3394252","title":"Leverage Variational Graph Representation for Model Poisoning on Federated Learning","display_name":"Leverage Variational Graph Representation for Model Poisoning on Federated Learning","publication_year":2024,"publication_date":"2024-05-03","ids":{"openalex":"https://openalex.org/W4396629473","doi":"https://doi.org/10.1109/tnnls.2024.3394252","pmid":"https://pubmed.ncbi.nlm.nih.gov/38700966"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3394252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3394252","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100399848","display_name":"Kai Li","orcid":"https://orcid.org/0000-0002-0517-2392"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kai Li","raw_affiliation_strings":["Department of Engineering, University of Cambridge, Cambridge, U.K","Real-Time and Embedded Computing Systems Research Center (CISTER), Porto, Portugal"],"raw_orcid":"https://orcid.org/0000-0002-0517-2392","affiliations":[{"raw_affiliation_string":"Department of Engineering, University of Cambridge, Cambridge, U.K","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"Real-Time and Embedded Computing Systems Research Center (CISTER), Porto, Portugal","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049765501","display_name":"Xin Yuan","orcid":"https://orcid.org/0000-0002-9167-1613"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"government","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xin Yuan","raw_affiliation_strings":["Digital Productivity and Services Flagship, Commonwealth Scientific and Industrial Research Organization (CSIRO), Marsfield, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0002-9167-1613","affiliations":[{"raw_affiliation_string":"Digital Productivity and Services Flagship, Commonwealth Scientific and Industrial Research Organization (CSIRO), Marsfield, NSW, Australia","institution_ids":["https://openalex.org/I1292875679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023908179","display_name":"Jingjing Zheng","orcid":"https://orcid.org/0000-0002-5728-9453"},"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":"Jingjing Zheng","raw_affiliation_strings":["Real-Time and Embedded Computing Systems Research Center (CISTER), Porto, Portugal","CyLab Security and Privacy Institute, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-5728-9453","affiliations":[{"raw_affiliation_string":"Real-Time and Embedded Computing Systems Research Center (CISTER), Porto, Portugal","institution_ids":[]},{"raw_affiliation_string":"CyLab Security and Privacy Institute, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101544825","display_name":"Wei Ni","orcid":"https://orcid.org/0000-0002-4933-594X"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"government","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Wei Ni","raw_affiliation_strings":["Digital Productivity and Services Flagship, Commonwealth Scientific and Industrial Research Organization (CSIRO), Marsfield, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0002-4933-594X","affiliations":[{"raw_affiliation_string":"Digital Productivity and Services Flagship, Commonwealth Scientific and Industrial Research Organization (CSIRO), Marsfield, NSW, Australia","institution_ids":["https://openalex.org/I1292875679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042212040","display_name":"Falko Dressler","orcid":"https://orcid.org/0000-0002-1989-1750"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Falko Dressler","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, TU Berlin, Berlin, Germany"],"raw_orcid":"https://orcid.org/0000-0002-1989-1750","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, TU Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086268677","display_name":"Abbas Jamalipour","orcid":"https://orcid.org/0000-0002-1807-7220"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Abbas Jamalipour","raw_affiliation_strings":["School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0002-1807-7220","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.1677,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.94588384,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"36","issue":"1","first_page":"116","last_page":"128"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9929999709129333,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9929999709129333,"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/leverage","display_name":"Leverage (statistics)","score":0.7358350157737732},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6810161471366882},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6633586883544922},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6066523194313049},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4978210926055908},{"id":"https://openalex.org/keywords/local-structure","display_name":"Local structure","score":0.4454975128173828},{"id":"https://openalex.org/keywords/attack-model","display_name":"Attack model","score":0.43706265091896057},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42407259345054626},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.42008909583091736},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39438021183013916},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3822765648365021},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.26324450969696045},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.21076470613479614}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7358350157737732},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6810161471366882},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6633586883544922},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6066523194313049},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4978210926055908},{"id":"https://openalex.org/C2986090443","wikidata":"https://www.wikidata.org/wiki/Q77870413","display_name":"Local structure","level":2,"score":0.4454975128173828},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.43706265091896057},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42407259345054626},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.42008909583091736},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39438021183013916},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3822765648365021},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.26324450969696045},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.21076470613479614},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C159467904","wikidata":"https://www.wikidata.org/wiki/Q2001702","display_name":"Chemical physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3394252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3394252","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:38700966","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38700966","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W97268080","https://openalex.org/W107619411","https://openalex.org/W1592670347","https://openalex.org/W1997120656","https://openalex.org/W2007339694","https://openalex.org/W2162986857","https://openalex.org/W2942655651","https://openalex.org/W2962763344","https://openalex.org/W2972209102","https://openalex.org/W2977090839","https://openalex.org/W2982302101","https://openalex.org/W3029523587","https://openalex.org/W3084847664","https://openalex.org/W3093773625","https://openalex.org/W3111919937","https://openalex.org/W3133814152","https://openalex.org/W3138153888","https://openalex.org/W3200256144","https://openalex.org/W3211470872","https://openalex.org/W4213110664","https://openalex.org/W4224316323","https://openalex.org/W4225764883","https://openalex.org/W4226524907","https://openalex.org/W4229455429","https://openalex.org/W4250589301","https://openalex.org/W4284893281","https://openalex.org/W4285554319","https://openalex.org/W4293195534","https://openalex.org/W4300991139","https://openalex.org/W4312996082","https://openalex.org/W4318822841","https://openalex.org/W4320235405","https://openalex.org/W4376478371","https://openalex.org/W4385079041","https://openalex.org/W6743688258","https://openalex.org/W6743821447","https://openalex.org/W6767032894","https://openalex.org/W6770634426","https://openalex.org/W6785153168"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3211393740","https://openalex.org/W3208049411","https://openalex.org/W3022908591","https://openalex.org/W4285706568","https://openalex.org/W4307079546","https://openalex.org/W4283317927","https://openalex.org/W3102631191"],"abstract_inverted_index":{"This":[0],"article":[1],"puts":[2],"forth":[3],"a":[4,104,137,160],"new":[5,17,105],"training":[6,45,81,132],"data-untethered":[7],"model":[8],"poisoning":[9],"(MP)":[10],"attack":[11,19,56,69,147],"on":[12,34],"federated":[13],"learning":[14],"(FL).":[15],"The":[16],"MP":[18],"extends":[20],"an":[21,50,123],"adversarial":[22,96],"variational":[23],"graph":[24,71,87,97],"autoencoder":[25],"(VGAE)":[26],"to":[27,43,53,66,110,163],"create":[28],"malicious":[29,91,113],"local":[30,37,77,92,114,129],"models":[31,38,78,93,115,130],"based":[32],"solely":[33],"the":[35,44,54,75,80,86,95,112,127,133,144,149,157],"benign":[36,76,100,128],"overheard":[39],"without":[40],"any":[41],"access":[42],"data":[46,82],"of":[47,126,151],"FL.":[48,164],"Such":[49],"advancement":[51],"leads":[52],"VGAE-MP":[55,68,146],"that":[57],"is":[58,108],"not":[59],"only":[60],"efficacious":[61],"but":[62],"also":[63],"remains":[64],"elusive":[65],"detection.":[67],"extracts":[70],"structural":[72],"correlations":[73],"among":[74],"and":[79,89,99,118,148],"features,":[83],"adversarially":[84],"regenerates":[85],"structure,":[88],"generates":[90],"using":[94,116],"structure":[98],"models'":[101],"features.":[102],"Moreover,":[103],"attacking":[106],"algorithm":[107],"presented":[109],"train":[111],"VGAE":[117],"sub-gradient":[119],"descent,":[120],"while":[121],"enabling":[122],"optimal":[124],"selection":[125],"for":[131],"VGAE.":[134],"Experiments":[135],"demonstrate":[136],"gradual":[138],"drop":[139],"in":[140,155],"FL":[141],"accuracy":[142],"under":[143],"proposed":[145],"ineffectiveness":[150],"existing":[152],"defense":[153],"mechanisms":[154],"detecting":[156],"attack,":[158],"posing":[159],"severe":[161],"threat":[162]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
