{"id":"https://openalex.org/W7151421125","doi":"https://doi.org/10.48550/arxiv.2604.03862","title":"SecureAFL: Secure Asynchronous Federated Learning","display_name":"SecureAFL: Secure Asynchronous Federated Learning","publication_year":2026,"publication_date":"2026-04-04","ids":{"openalex":"https://openalex.org/W7151421125","doi":"https://doi.org/10.48550/arxiv.2604.03862"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.03862","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.03862","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.2604.03862","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133076790","display_name":"Anjun Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Anjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133082848","display_name":"Feng Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Feng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133131374","display_name":"Zhenglin Wan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wan, Zhenglin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133131043","display_name":"Yueyang Quan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Quan, Yueyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133115339","display_name":"Zhuqing Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zhuqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133100374","display_name":"Minghong Fang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang, Minghong","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":0.9375,"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":0.9375,"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":0.016899999231100082,"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/T10237","display_name":"Cryptography and Data Security","score":0.00839999970048666,"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/asynchronous-communication","display_name":"Asynchronous communication","score":0.9229999780654907},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.8180000185966492},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6680999994277954},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.43790000677108765},{"id":"https://openalex.org/keywords/asynchronous-learning","display_name":"Asynchronous learning","score":0.40959998965263367},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.3828999996185303}],"concepts":[{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.9229999780654907},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8360999822616577},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.8180000185966492},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6680999994277954},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4855000078678131},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.43790000677108765},{"id":"https://openalex.org/C2777072894","wikidata":"https://www.wikidata.org/wiki/Q4812204","display_name":"Asynchronous learning","level":5,"score":0.40959998965263367},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.40070000290870667},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3828999996185303},{"id":"https://openalex.org/C2779019669","wikidata":"https://www.wikidata.org/wiki/Q25203946","display_name":"Asynchrony (computer programming)","level":3,"score":0.3264999985694885},{"id":"https://openalex.org/C2779965156","wikidata":"https://www.wikidata.org/wiki/Q5227350","display_name":"Data sharing","level":3,"score":0.27059999108314514},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2662999927997589},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.25870001316070557},{"id":"https://openalex.org/C164554305","wikidata":"https://www.wikidata.org/wiki/Q71550","display_name":"Application server","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.03862","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.03862","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.2604.03862","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.03862","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":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.45128634572029114}],"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],"learning":[1,12],"(FL)":[2],"enables":[3],"multiple":[4],"clients":[5,41],"to":[6,45,69,94,111,130,167],"collaboratively":[7],"train":[8],"a":[9,15,29],"global":[10,48,72],"machine":[11],"model":[13,37,73,80],"via":[14],"server":[16,34,68,118],"without":[17],"sharing":[18],"their":[19],"private":[20],"training":[21],"data.":[22],"In":[23,120],"traditional":[24],"FL,":[25],"the":[26,33,47,56,62,67,71,85,139,152,169,181],"system":[27],"follows":[28],"synchronous":[30,51],"approach,":[31],"where":[32],"waits":[35],"for":[36,100],"updates":[38,149],"from":[39],"numerous":[40],"before":[42],"aggregating":[43],"them":[44],"update":[46,70],"model.":[49],"However,":[50],"FL":[52,64,90,102,133,143],"is":[53],"hindered":[54],"by":[55,144],"straggler":[57],"problem.":[58],"To":[59],"address":[60],"this,":[61],"asynchronous":[63,89,101,132,142],"architecture":[65],"allows":[66],"immediately":[74],"upon":[75],"receiving":[76],"any":[77],"client's":[78],"local":[79],"update.":[81],"Despite":[82],"its":[83],"advantages,":[84],"decentralized":[86],"nature":[87],"of":[88,141,154,183],"makes":[91],"it":[92,158],"vulnerable":[93],"poisoning":[95,135],"attacks.":[96,136],"Several":[97],"defenses":[98],"tailored":[99],"have":[103],"been":[104],"proposed,":[105],"but":[106],"these":[107],"mechanisms":[108],"remain":[109],"susceptible":[110],"advanced":[112],"attacks":[113],"or":[114],"rely":[115],"on":[116,176],"unrealistic":[117],"assumptions.":[119],"this":[121],"paper,":[122],"we":[123],"introduce":[124],"SecureAFL,":[125],"an":[126],"innovative":[127],"framework":[128],"designed":[129],"secure":[131],"against":[134],"SecureAFL":[137],"improves":[138],"robustness":[140],"detecting":[145],"and":[146,171],"discarding":[147],"anomalous":[148],"while":[150],"estimating":[151],"contributions":[153],"missing":[155],"clients.":[156],"Additionally,":[157],"utilizes":[159],"Byzantine-robust":[160],"aggregation":[161],"techniques,":[162],"such":[163],"as":[164],"coordinate-wise":[165],"median,":[166],"integrate":[168],"received":[170],"estimated":[172],"updates.":[173],"Extensive":[174],"experiments":[175],"various":[177],"real-world":[178],"datasets":[179],"demonstrate":[180],"effectiveness":[182],"SecureAFL.":[184]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-08T00:00:00"}
