{"id":"https://openalex.org/W4417131378","doi":"https://doi.org/10.1109/ton.2025.3636809","title":"Cooperative Decentralized Backdoor Attacks on Vertical Federated Learning","display_name":"Cooperative Decentralized Backdoor Attacks on Vertical Federated Learning","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W4417131378","doi":"https://doi.org/10.1109/ton.2025.3636809"},"language":null,"primary_location":{"id":"doi:10.1109/ton.2025.3636809","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ton.2025.3636809","pdf_url":null,"source":{"id":"https://openalex.org/S5407042750","display_name":"IEEE Transactions on Networking","issn_l":"2998-4157","issn":["2998-4157"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Networking","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/A5071822844","display_name":"Seohyun Lee","orcid":"https://orcid.org/0009-0005-3472-1847"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Seohyun Lee","raw_affiliation_strings":["Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0009-0005-3472-1847","affiliations":[{"raw_affiliation_string":"Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012031491","display_name":"Wenzhi Fang","orcid":"https://orcid.org/0000-0003-3013-8978"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenzhi Fang","raw_affiliation_strings":["Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0003-3013-8978","affiliations":[{"raw_affiliation_string":"Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029951257","display_name":"Anindya Bijoy Das","orcid":"https://orcid.org/0000-0002-3615-7400"},"institutions":[{"id":"https://openalex.org/I110152177","display_name":"University of Akron","ror":"https://ror.org/02kyckx55","country_code":"US","type":"education","lineage":["https://openalex.org/I110152177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anindya Bijoy Das","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of Akron, Akron, OH, USA"],"raw_orcid":"https://orcid.org/0000-0002-3615-7400","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Akron, Akron, OH, USA","institution_ids":["https://openalex.org/I110152177"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059750214","display_name":"Seyyedali Hosseinalipour","orcid":"https://orcid.org/0000-0003-4266-4000"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Seyyedali Hosseinalipour","raw_affiliation_strings":["Department of Electrical Engineering, University at Buffalo-SUNY, Buffalo, NY, USA"],"raw_orcid":"https://orcid.org/0000-0003-4266-4000","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University at Buffalo-SUNY, Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001355478","display_name":"David J. Love","orcid":"https://orcid.org/0000-0001-5922-4787"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David J. Love","raw_affiliation_strings":["Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0001-5922-4787","affiliations":[{"raw_affiliation_string":"Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020399355","display_name":"Christopher G. Brinton","orcid":"https://orcid.org/0000-0003-2771-3521"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher G. Brinton","raw_affiliation_strings":["Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0003-2771-3521","affiliations":[{"raw_affiliation_string":"Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5071822844"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":2.1733,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.91475149,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"34","issue":null,"first_page":"2004","last_page":"2019"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.6527000069618225,"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":0.6527000069618225,"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":0.24079999327659607,"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":0.014399999752640724,"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/backdoor","display_name":"Backdoor","score":0.9689000248908997},{"id":"https://openalex.org/keywords/collusion","display_name":"Collusion","score":0.6263999938964844},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.6164000034332275},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.47279998660087585},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.43220001459121704},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.41350001096725464},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.3522999882698059}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9689000248908997},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6973999738693237},{"id":"https://openalex.org/C2781198186","wikidata":"https://www.wikidata.org/wiki/Q701521","display_name":"Collusion","level":2,"score":0.6263999938964844},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.6164000034332275},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.47279998660087585},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.45680001378059387},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.43220001459121704},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.41350001096725464},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35600000619888306},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.3522999882698059},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3294000029563904},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30799999833106995},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27320000529289246},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.26440000534057617},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ton.2025.3636809","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ton.2025.3636809","pdf_url":null,"source":{"id":"https://openalex.org/S5407042750","display_name":"IEEE Transactions on Networking","issn_l":"2998-4157","issn":["2998-4157"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Networking","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1731802535","display_name":null,"funder_award_id":"ECCS-2512911","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3953276932","display_name":null,"funder_award_id":"CNS-2212565","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6776902378","display_name":null,"funder_award_id":"N00014-22-1-2305","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G7606552644","display_name":null,"funder_award_id":"N00014-21-1-2472","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1587744656","https://openalex.org/W1965555277","https://openalex.org/W2001610032","https://openalex.org/W2007339694","https://openalex.org/W2096733369","https://openalex.org/W2227557434","https://openalex.org/W2907553065","https://openalex.org/W2909431601","https://openalex.org/W2940040251","https://openalex.org/W2942091739","https://openalex.org/W2963433607","https://openalex.org/W2965721472","https://openalex.org/W3047079385","https://openalex.org/W3094542121","https://openalex.org/W3096831136","https://openalex.org/W3157850870","https://openalex.org/W3178445113","https://openalex.org/W3200089916","https://openalex.org/W4226479888","https://openalex.org/W4283265085","https://openalex.org/W4311415873","https://openalex.org/W4312798861","https://openalex.org/W4319300019","https://openalex.org/W4361770927","https://openalex.org/W4376464626","https://openalex.org/W4382237486","https://openalex.org/W4386804452","https://openalex.org/W4388206624","https://openalex.org/W4390889741","https://openalex.org/W4391250546","https://openalex.org/W4391430623","https://openalex.org/W4391529040","https://openalex.org/W4392024995","https://openalex.org/W4393161237","https://openalex.org/W4401023496","https://openalex.org/W4402156734","https://openalex.org/W4402264407","https://openalex.org/W4406461648","https://openalex.org/W4409640924"],"related_works":[],"abstract_inverted_index":{"Federated":[0],"learning":[1],"(FL)":[2],"is":[3],"vulnerable":[4],"to":[5,118],"backdoor":[6,63,148,175],"attacks,":[7],"where":[8,41],"adversaries":[9,85,103],"alter":[10],"model":[11,95],"behavior":[12],"on":[13,65,72,150,205],"target":[14],"classification":[15],"labels":[16],"by":[17,153],"embedding":[18],"triggers":[19],"into":[20],"data":[21],"samples.":[22],"While":[23],"these":[24],"attacks":[25],"have":[26],"received":[27],"considerable":[28],"attention":[29],"in":[30],"horizontal":[31],"FL,":[32],"they":[33],"are":[34],"less":[35],"understood":[36],"for":[37,86,124,157,186],"vertical":[38],"FL":[39],"(VFL),":[40],"devices":[42],"hold":[43],"different":[44],"features":[45],"of":[46,147,203],"the":[47,51,54,76,111,128,136,139,145,158,187,201],"samples,":[48],"and":[49,78,89],"only":[50],"server":[52,77,137,195],"holds":[53],"labels.":[55],"In":[56],"this":[57],"work,":[58],"we":[59,162],"propose":[60,122],"a":[61,154],"novel":[62],"attack":[64,172,206],"VFL":[66,151,176],"which":[67,102,116,161],"(i)":[68],"does":[69],"not":[70,193],"rely":[71],"gradient":[73],"information":[74],"from":[75],"(ii)":[79],"considers":[80],"potential":[81],"collusion":[82,204],"among":[83],"multiple":[84],"sample":[87],"selection":[88],"trigger":[90,125],"embedding.":[91],"Our":[92,141],"label":[93],"inference":[94],"augments":[96],"variational":[97],"autoencoders":[98],"with":[99,130,173],"metric":[100],"learning,":[101],"can":[104],"train":[105],"locally.":[106],"A":[107],"consensus":[108],"process":[109],"over":[110],"adversary":[112],"graph":[113],"topology":[114],"determines":[115],"datapoints":[117],"poison.":[119],"We":[120,167],"further":[121],"methods":[123],"splitting":[126],"across":[127],"adversaries,":[129],"an":[131],"intensity-based":[132],"implantation":[133],"scheme":[134],"skewing":[135],"towards":[138],"trigger.":[140],"convergence":[142],"analysis":[143],"reveals":[144],"impact":[146,202],"perturbations":[149],"indicated":[152],"stationarity":[155],"gap":[156],"trained":[159],"model,":[160],"verify":[163,200],"empirically":[164],"as":[165],"well.":[166],"conduct":[168],"experiments":[169],"comparing":[170],"our":[171,198],"recent":[174],"approaches,":[177],"finding":[178],"that":[179],"ours":[180],"obtains":[181],"significantly":[182],"higher":[183],"success":[184],"rates":[185],"same":[188],"main":[189],"task":[190],"performance":[191],"despite":[192],"using":[194],"information.":[196],"Additionally,":[197],"results":[199],"performance.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-01-10T23:39:48.068659","created_date":"2025-12-08T00:00:00"}
