{"id":"https://openalex.org/W7138858887","doi":"https://doi.org/10.1609/aaai.v40i42.40859","title":"FILTER: A Framework for Defending Against Backdoor Attacks in Vertical Federated Learning","display_name":"FILTER: A Framework for Defending Against Backdoor Attacks in Vertical Federated Learning","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138858887","doi":"https://doi.org/10.1609/aaai.v40i42.40859"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i42.40859","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i42.40859","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/40859/44820","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/40859/44820","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034373978","display_name":"Z. Hu","orcid":"https://orcid.org/0000-0001-8209-4343"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhanyi Hu","raw_affiliation_strings":["East China Normal University"],"affiliations":[{"raw_affiliation_string":"East China Normal University","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130003616","display_name":"Cen Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cen Chen","raw_affiliation_strings":["East China Normal University"],"affiliations":[{"raw_affiliation_string":"East China Normal University","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129898860","display_name":"Yanhao Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanhao Wang","raw_affiliation_strings":["East China Normal University"],"affiliations":[{"raw_affiliation_string":"East China Normal University","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5034373978"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.734683,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"42","first_page":"35490","last_page":"35499"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.5351999998092651,"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":0.5351999998092651,"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":0.35109999775886536,"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":0.03060000017285347,"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":0.9986000061035156},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.38359999656677246},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.3598000109195709},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.30979999899864197},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.250900000333786}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9986000061035156},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6614999771118164},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.527400016784668},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.400299996137619},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.38359999656677246},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3598000109195709},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32170000672340393},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.250900000333786},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.24779999256134033}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i42.40859","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i42.40859","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/40859/44820","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i42.40859","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i42.40859","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/40859/44820","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1401240932","display_name":null,"funder_award_id":"62202169","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5733390078","display_name":null,"funder_award_id":"Grant Nos.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8914462144","display_name":null,"funder_award_id":"62202170","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138858887.pdf","grobid_xml":"https://content.openalex.org/works/W7138858887.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Vertical":[0],"Federated":[1],"Learning":[2],"(VFL)":[3],"is":[4],"a":[5,94,133],"distributed":[6],"machine":[7,43],"learning":[8,44],"paradigm":[9],"in":[10,26,78,101,112,122,143],"which":[11,136],"participants":[12],"train":[13],"models":[14,182],"with":[15],"vertically":[16],"partitioned":[17],"data.":[18],"Many":[19],"previous":[20],"studies":[21],"have":[22],"identified":[23],"backdoor":[24,55,76,99,120,158],"vulnerabilities":[25],"VFL":[27,48,79,102,108],"systems.":[28],"However,":[29],"limited":[30],"effort":[31],"has":[32],"been":[33],"devoted":[34],"to":[35,103,178],"developing":[36],"defenses":[37,74],"against":[38,54,75,98,155],"such":[39,185],"attacks.":[40],"Unlike":[41],"centralized":[42],"or":[45],"horizontal":[46],"FL,":[47],"poses":[49],"new":[50],"challenges":[51],"for":[52,96],"defending":[53,97],"attacks,":[56,159],"particularly":[57],"because":[58],"the":[59,65,81,87,105,113,166,181],"central":[60],"server":[61],"lacks":[62],"control":[63],"over":[64],"entire":[66],"model.":[67],"In":[68],"this":[69],"paper,":[70],"we":[71,91,160],"first":[72],"explore":[73],"attacks":[77,100,170],"when":[80],"attacker":[82],"possesses":[83],"sufficient":[84],"knowledge":[85],"of":[86,107,115,146,169,180],"label":[88],"information.":[89],"Specifically,":[90],"propose":[92],"FILTER,":[93],"framework":[95],"ensure":[104],"integrity":[106],"systems":[109],"during":[110],"training":[111],"presence":[114],"malicious":[116],"participants.":[117],"To":[118],"address":[119],"risks":[121],"VFL,":[123],"it":[124],"incorporates":[125],"two":[126],"novel":[127],"filters:":[128],"an":[129],"embedding-based":[130],"filter":[131],"and":[132,139],"loss-based":[134],"filter,":[135],"effectively":[137],"identify":[138],"remove":[140],"poisoned":[141],"samples":[142],"later":[144],"stages":[145],"training.":[147],"Through":[148],"extensive":[149],"experiments":[150],"on":[151,174],"five":[152],"benchmark":[153],"datasets":[154],"four":[156],"state-of-the-art":[157],"demonstrate":[161],"that":[162,179],"FILTER":[163],"significantly":[164],"reduces":[165],"success":[167],"rate":[168],"while":[171],"maintaining":[172],"accuracy":[173],"clean":[175],"data":[176],"close":[177],"trained":[183],"without":[184],"defenses.":[186]},"counts_by_year":[],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2026-03-20T00:00:00"}
