{"id":"https://openalex.org/W7133296365","doi":"https://doi.org/10.48550/arxiv.2603.00516","title":"ProtegoFed: Backdoor-Free Federated Instruction Tuning with Interspersed Poisoned Data","display_name":"ProtegoFed: Backdoor-Free Federated Instruction Tuning with Interspersed Poisoned Data","publication_year":2026,"publication_date":"2026-02-28","ids":{"openalex":"https://openalex.org/W7133296365","doi":"https://doi.org/10.48550/arxiv.2603.00516"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.00516","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00516","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.00516","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127944024","display_name":"Haodong Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Haodong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127886034","display_name":"Jinming Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Jinming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127965701","display_name":"Zhaomin Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Zhaomin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100585973","display_name":"Zongru Wu","orcid":"https://orcid.org/0000-0002-5387-7821"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Zongru","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127887392","display_name":"Wei Du","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128021735","display_name":"Junyi Hou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hou, Junyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127905760","display_name":"Caibei Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Caibei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127910607","display_name":"Zhuosheng Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zhuosheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127941743","display_name":"Bingsheng He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Bingsheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127983382","display_name":"Gongshen Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Gongshen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.451200008392334,"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":0.451200008392334,"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":0.16099999845027924,"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":0.05649999901652336,"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/identification","display_name":"Identification (biology)","score":0.6004999876022339},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5343999862670898},{"id":"https://openalex.org/keywords/data-sharing","display_name":"Data sharing","score":0.5130000114440918},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.42170000076293945},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.41819998621940613},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4041000008583069}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7299000024795532},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6004999876022339},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5343999862670898},{"id":"https://openalex.org/C2779965156","wikidata":"https://www.wikidata.org/wiki/Q5227350","display_name":"Data sharing","level":3,"score":0.5130000114440918},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.487199991941452},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.42170000076293945},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.41819998621940613},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4041000008583069},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.3977999985218048},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3758000135421753},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.32589998841285706},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.2646999955177307}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.00516","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00516","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.00516","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00516","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.42261165380477905}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Federated":[0],"Instruction":[1],"Tuning":[2],"(FIT)":[3],"enables":[4],"collaborative":[5,104,144],"instruction":[6],"tuning":[7],"of":[8,24,96,146,190],"large":[9],"language":[10],"models":[11],"across":[12,54,149,172],"multiple":[13],"organizations":[14],"(clients)":[15],"in":[16,49,69,122],"a":[17,127,137],"cross-silo":[18],"setting":[19],"without":[20],"requiring":[21],"the":[22,33,59,93,123,157,175,194,205],"sharing":[23],"private":[25],"instructions.":[26],"Recent":[27],"findings":[28],"on":[29,179,204],"natural":[30],"backdoors":[31],"and":[32,46,102,166,201],"existing":[34,73],"training":[35],"data":[36,79,171],"collection":[37],"method":[38],"suggest":[39],"that":[40,72,142,162,184],"poisoned":[41,78,97,113,132,147,170,191],"samples":[42,98,148],"may":[43],"be":[44],"pervasive":[45],"inadvertently":[47],"embedded":[48],"real-world":[50],"datasets,":[51],"potentially":[52],"distributed":[53],"all":[55,83],"clients,":[56],"even":[57,167],"if":[58],"clients":[60,108,173],"are":[61,75,109],"benign.":[62],"This":[63],"work":[64],"systematically":[65],"examine":[66],"this":[67,86,153],"threat":[68],"FIT,":[70],"demonstrating":[71],"defenses":[74],"ineffective":[76],"when":[77,106],"is":[80,209],"interspersed":[81,169],"among":[82],"clients.":[84,150],"Addressing":[85],"challenge":[87],"entails":[88],"two":[89],"major":[90],"difficulties:":[91],"identifying":[92],"distinctive":[94],"characteristics":[95],"at":[99,211],"each":[100],"client":[101],"enabling":[103],"defense":[105],"some":[107],"heavily":[110],"dominated":[111],"by":[112],"samples.":[114],"To":[115],"address":[116],"these":[117],"difficulties,":[118],"we":[119],"identify":[120],"gradients":[121],"frequency":[124],"domain":[125],"as":[126],"robust":[128],"signal":[129],"to":[130,198],"distinguish":[131],"data.":[133],"We":[134],"further":[135],"propose":[136],"global":[138],"secondary":[139],"clustering":[140],"mechanism":[141],"facilitates":[143],"identification":[145],"In":[151],"summary,":[152],"paper":[154],"introduces":[155],"ProtegoFed,":[156],"first":[158],"backdoor-free":[159],"FIT":[160],"framework":[161],"accurately":[163],"detects,":[164],"removes,":[165],"purifies":[168],"during":[174],"training.":[176],"Experimental":[177],"results":[178],"four":[180],"FL":[181],"datasets":[182],"show":[183],"ProtegoFed":[185],"identifies":[186],"$92.00\\%":[187],"\\sim":[188],"100.00\\%$":[189],"samples,":[192],"reduces":[193],"attack":[195],"success":[196],"rate":[197],"almost":[199],"zero,":[200],"maintains":[202],"utility":[203],"main":[206],"task.":[207],"Code":[208],"available":[210],"https://github.com/dongdongzhaoUP/ProtegoFed.":[212]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-04T00:00:00"}