{"id":"https://openalex.org/W7127136413","doi":"https://doi.org/10.1109/trustcom66490.2025.00034","title":"Buffer is All You Need: Defending Federated Learning against Backdoor Attacks under Non-iids via Buffering","display_name":"Buffer is All You Need: Defending Federated Learning against Backdoor Attacks under Non-iids via Buffering","publication_year":2025,"publication_date":"2025-11-14","ids":{"openalex":"https://openalex.org/W7127136413","doi":"https://doi.org/10.1109/trustcom66490.2025.00034"},"language":null,"primary_location":{"id":"doi:10.1109/trustcom66490.2025.00034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/trustcom66490.2025.00034","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 24th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5124756238","display_name":"Xingyu Lyu","orcid":null},"institutions":[{"id":"https://openalex.org/I133738476","display_name":"University of Massachusetts Lowell","ror":"https://ror.org/03hamhx47","country_code":"US","type":"education","lineage":["https://openalex.org/I133738476"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xingyu Lyu","raw_affiliation_strings":["University of Massachusetts,Lowell,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts,Lowell,USA","institution_ids":["https://openalex.org/I133738476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113291954","display_name":"Ning Wang","orcid":"https://orcid.org/0009-0005-1718-8550"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]},{"id":"https://openalex.org/I75821886","display_name":"University of South Florida St. Petersburg","ror":"https://ror.org/016gp6x28","country_code":"US","type":"education","lineage":["https://openalex.org/I75821886"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ning Wang","raw_affiliation_strings":["University of South,Florida,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South,Florida,USA","institution_ids":["https://openalex.org/I2613432","https://openalex.org/I75821886"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112329513","display_name":"Yang Xiao","orcid":"https://orcid.org/0009-0009-4524-1805"},"institutions":[{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Xiao","raw_affiliation_strings":["University of Kentucky,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Kentucky,USA","institution_ids":["https://openalex.org/I143302722"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124813611","display_name":"Shixiong Li","orcid":null},"institutions":[{"id":"https://openalex.org/I133738476","display_name":"University of Massachusetts Lowell","ror":"https://ror.org/03hamhx47","country_code":"US","type":"education","lineage":["https://openalex.org/I133738476"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shixiong Li","raw_affiliation_strings":["University of Massachusetts,Lowell,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts,Lowell,USA","institution_ids":["https://openalex.org/I133738476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455316","display_name":"Tao Li","orcid":"https://orcid.org/0000-0002-5333-0586"},"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":"Tao Li","raw_affiliation_strings":["Purdue University,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048737692","display_name":"Danjue Chen","orcid":"https://orcid.org/0000-0003-4170-0276"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danjue Chen","raw_affiliation_strings":["North Carolina State University,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Carolina State University,USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124756574","display_name":"Yimin Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I133738476","display_name":"University of Massachusetts Lowell","ror":"https://ror.org/03hamhx47","country_code":"US","type":"education","lineage":["https://openalex.org/I133738476"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yimin Chen","raw_affiliation_strings":["University of Massachusetts,Lowell,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts,Lowell,USA","institution_ids":["https://openalex.org/I133738476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.346,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.94072173,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"236","last_page":"243"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.5266000032424927,"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":0.5266000032424927,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.2953999936580658,"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":0.02850000001490116,"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":0.993399977684021},{"id":"https://openalex.org/keywords/upload","display_name":"Upload","score":0.6463000178337097},{"id":"https://openalex.org/keywords/safer","display_name":"SAFER","score":0.5375000238418579},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5185999870300293},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.4142000079154968},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.34540000557899475},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.32989999651908875}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.993399977684021},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7962999939918518},{"id":"https://openalex.org/C71901391","wikidata":"https://www.wikidata.org/wiki/Q7126699","display_name":"Upload","level":2,"score":0.6463000178337097},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.6157000064849854},{"id":"https://openalex.org/C2776654903","wikidata":"https://www.wikidata.org/wiki/Q2601463","display_name":"SAFER","level":2,"score":0.5375000238418579},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5185999870300293},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.4142000079154968},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.34540000557899475},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.32989999651908875},{"id":"https://openalex.org/C73301696","wikidata":"https://www.wikidata.org/wiki/Q5469984","display_name":"Formalism (music)","level":3,"score":0.32190001010894775},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3156000077724457},{"id":"https://openalex.org/C40842320","wikidata":"https://www.wikidata.org/wiki/Q19423","display_name":"Buffer overflow","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2930999994277954},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C40305131","wikidata":"https://www.wikidata.org/wiki/Q2616305","display_name":"Obfuscation","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.2578999996185303}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/trustcom66490.2025.00034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/trustcom66490.2025.00034","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 24th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W3138597937","https://openalex.org/W4281398987","https://openalex.org/W4287332481","https://openalex.org/W4290948380","https://openalex.org/W4388856889","https://openalex.org/W4390190173","https://openalex.org/W4390698442","https://openalex.org/W4391724758","https://openalex.org/W4391724779","https://openalex.org/W4402264021","https://openalex.org/W4403937356","https://openalex.org/W4408565045","https://openalex.org/W4408750008","https://openalex.org/W4413822613","https://openalex.org/W7117900650"],"related_works":[],"abstract_inverted_index":{"Federated":[0],"Learning":[1],"(FL)":[2],"is":[3,21,81,98,151],"a":[4,12,128,136],"popular":[5],"paradigm":[6],"enabling":[7],"clients":[8],"to":[9,23,30,95,121,134],"jointly":[10],"train":[11],"global":[13],"model":[14,39,130],"without":[15],"sharing":[16],"raw":[17],"data.":[18],"However,":[19],"FL":[20],"known":[22],"be":[24,106],"vulnerable":[25],"towards":[26],"backdoor":[27,70,115],"attacks":[28,71,116],"due":[29],"its":[31],"distributed":[32],"nature.":[33],"As":[34],"participants,":[35],"attackers":[36],"can":[37,105],"upload":[38],"updates":[40],"that":[41,82,103,144],"effectively":[42],"compromise":[43],"FL.":[44,63],"More":[45],"critically,":[46],"existing":[47],"defenses":[48,80],"are":[49],"mostly":[50],"designed":[51],"under":[52,73],"independent-and-identically-distributed":[53],"(iid)":[54],"settings,":[55],"hence":[56],"neglecting":[57],"the":[58,85,122],"fundamental":[59],"non-iid":[60],"characteristic":[61],"of":[62,125],"Here":[64],"we":[65],"propose":[66],"FLBuff":[67,97,145],"for":[68,78],"tackling":[69],"even":[72],"non-iids.":[74],"The":[75],"main":[76],"challenge":[77],"such":[79],"non-iids":[83,104],"shorten":[84],"distance":[86],"between":[87],"benign":[88],"and":[89],"malicious":[90],"updates,":[91],"rendering":[92],"them":[93],"harder":[94],"separate.":[96],"inspired":[99],"by":[100],"our":[101],"insight":[102],"modeled":[107],"as":[108,117],"omni-directional":[109],"expansion":[110],"in":[111],"representation":[112],"space":[113],"while":[114],"uni-directional.":[118],"This":[119],"leads":[120],"key":[123],"design":[124],"FLBuff,":[126],"i.e.,":[127],"supervised-contrastive-learning":[129],"extracting":[131],"penultimate-layer":[132],"representations":[133],"create":[135],"large":[137],"in-between":[138],"buffer":[139],"layer.":[140],"Comprehensive":[141],"evaluations":[142],"demonstrate":[143],"consistently":[146],"outperforms":[147],"state-of-the-art":[148],"defenses.":[149],"Code":[150],"at":[152],"https://github.com/xingyushu/FLBuff.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-02-03T00:00:00"}
