{"id":"https://openalex.org/W4404788571","doi":"https://doi.org/10.1145/3652892.3700787","title":"AsyncFilter: Detecting Poisoning Attacks in Asynchronous Federated Learning","display_name":"AsyncFilter: Detecting Poisoning Attacks in Asynchronous Federated Learning","publication_year":2024,"publication_date":"2024-11-27","ids":{"openalex":"https://openalex.org/W4404788571","doi":"https://doi.org/10.1145/3652892.3700787"},"language":"en","primary_location":{"id":"doi:10.1145/3652892.3700787","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3652892.3700787","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th International Middleware Conference","raw_type":"proceedings-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/A5085760909","display_name":"Yufei Kang","orcid":"https://orcid.org/0000-0001-9406-8775"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Yufei Kang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canda"],"raw_orcid":"https://orcid.org/0000-0001-9406-8775","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canda","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083596391","display_name":"Baochun Li","orcid":"https://orcid.org/0000-0003-2404-0974"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Baochun Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada"],"raw_orcid":"https://orcid.org/0000-0003-2404-0974","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5085760909"],"corresponding_institution_ids":["https://openalex.org/I185261750"],"apc_list":null,"apc_paid":null,"fwci":0.6623,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.76461413,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"481","last_page":"493"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9980000257492065,"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":0.9980000257492065,"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/T10363","display_name":"Low-power high-performance VLSI design","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.9898999929428101,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/computer-science","display_name":"Computer science","score":0.7663139700889587},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.6417412161827087},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.5936527252197266},{"id":"https://openalex.org/keywords/asynchronous-learning","display_name":"Asynchronous learning","score":0.4191972017288208},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2813527584075928},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.058826178312301636},{"id":"https://openalex.org/keywords/synchronous-learning","display_name":"Synchronous learning","score":0.04746803641319275}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7663139700889587},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.6417412161827087},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.5936527252197266},{"id":"https://openalex.org/C2777072894","wikidata":"https://www.wikidata.org/wiki/Q4812204","display_name":"Asynchronous learning","level":5,"score":0.4191972017288208},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2813527584075928},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.058826178312301636},{"id":"https://openalex.org/C19122763","wikidata":"https://www.wikidata.org/wiki/Q7662215","display_name":"Synchronous learning","level":4,"score":0.04746803641319275},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C51672120","wikidata":"https://www.wikidata.org/wiki/Q303446","display_name":"Cooperative learning","level":3,"score":0.0},{"id":"https://openalex.org/C88610354","wikidata":"https://www.wikidata.org/wiki/Q1813494","display_name":"Teaching method","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3652892.3700787","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3652892.3700787","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th International Middleware Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2007339694","https://openalex.org/W2112796928","https://openalex.org/W2187089797","https://openalex.org/W3138153888","https://openalex.org/W4283837358","https://openalex.org/W4290948380","https://openalex.org/W4311165757","https://openalex.org/W4382318866"],"related_works":["https://openalex.org/W4226047841","https://openalex.org/W2156559761","https://openalex.org/W3020208395","https://openalex.org/W2496167052","https://openalex.org/W1956936791","https://openalex.org/W2041343407","https://openalex.org/W4401821536","https://openalex.org/W2058515809","https://openalex.org/W4295242624","https://openalex.org/W2946278724"],"abstract_inverted_index":{"Federated":[0],"learning":[1,10,120],"has":[2,67],"garnered":[3],"substantial":[4],"research":[5,48],"attention":[6],"as":[7,110,178,180],"a":[8,70,111],"privacy-preserving":[9],"paradigm.":[11],"Nonetheless,":[12],"its":[13],"inherently":[14],"distributed":[15],"architecture,":[16],"especially":[17],"in":[18,105,162,169],"asynchronous":[19,106],"settings,":[20],"poses":[21],"vulnerabilities":[22],"to":[23,69,148],"model":[24,38,140,143,166],"poisoning":[25,103,144,167],"attacks.":[26],"In":[27,73],"such":[28],"scenarios,":[29,84],"malicious":[30],"clients":[31],"compromise":[32],"the":[33,36,61,65,88,115,119],"integrity":[34],"of":[35],"global":[37,139],"by":[39,122,146],"transmitting":[40],"manipulated":[41],"updates.":[42],"To":[43],"tackle":[44],"this":[45,74],"issue,":[46],"previous":[47],"efforts":[49],"like":[50],"AFLGuard":[51],"and":[52,91,125,152,164,175],"Zeno++":[53],"have":[54],"made":[55],"strides":[56],"but":[57],"often":[58],"hinge":[59],"on":[60,114],"impractical":[62],"assumption":[63],"that":[64],"server":[66],"access":[68],"clean":[71],"dataset.":[72],"study,":[75],"we":[76,96],"delve":[77],"into":[78],"practical":[79],"solutions":[80],"tailored":[81],"for":[82],"real-world":[83,134],"minimizing":[85],"assumptions":[86],"about":[87],"server's":[89],"capabilities":[90,161],"accommodating":[92],"varying":[93,181],"settings.":[94],"Specifically,":[95],"propose":[97],"AsyncFilter":[98,117,136,158],"module,":[99],"which":[100],"defends":[101],"against":[102,142],"attacks":[104,145,168],"federated":[107],"learning.":[108],"Functioning":[109],"plug-and-play":[112],"module":[113],"server,":[116],"enhances":[118,138],"process":[121],"statistically":[123],"identifying":[124],"filtering":[126],"out":[127],"poisoned":[128],"updates":[129],"during":[130],"training.":[131],"On":[132],"four":[133],"datasets,":[135],"effectively":[137],"accuracy":[141],"up":[147],"7%,":[149],"20%,":[150],"16%":[151],"39%":[153],"respectively.":[154],"Through":[155],"extensive":[156],"evaluation,":[157],"demonstrates":[159],"robust":[160],"detecting":[163],"mitigating":[165],"various":[170],"scenarios":[171],"encompassing":[172],"diverse":[173],"data":[174],"system":[176],"heterogeneity,":[177],"well":[179],"attacker":[182],"presence.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}