{"id":"https://openalex.org/W4296857612","doi":"https://doi.org/10.1145/3523062","title":"Defending against Poisoning Backdoor Attacks on Federated Meta-learning","display_name":"Defending against Poisoning Backdoor Attacks on Federated Meta-learning","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4296857612","doi":"https://doi.org/10.1145/3523062"},"language":"en","primary_location":{"id":"doi:10.1145/3523062","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3523062","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3523062","source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3523062","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089582317","display_name":"Chien-Lun Chen","orcid":"https://orcid.org/0000-0001-8904-4760"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chien-Lun Chen","raw_affiliation_strings":["University of Southern California, Los Angeles, California, USA"],"raw_orcid":"https://orcid.org/0000-0001-8904-4760","affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, California, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061117202","display_name":"Sara Babakniya","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sara Babakniya","raw_affiliation_strings":["University of Southern California, Los Angeles, California, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, California, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036380703","display_name":"Marco Paolieri","orcid":"https://orcid.org/0000-0001-5110-203X"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marco Paolieri","raw_affiliation_strings":["University of Southern California, Los Angeles, California, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, California, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081582862","display_name":"Leana Golubchik","orcid":"https://orcid.org/0000-0001-8353-5040"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leana Golubchik","raw_affiliation_strings":["University of Southern California, Los Angeles, California, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, California, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":1.4433,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.8461002,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"13","issue":"5","first_page":"1","last_page":"25"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9850000143051147,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.920799970626831,"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":0.9972623586654663},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.866820752620697},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6100866794586182},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.5918685793876648},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.5275461673736572},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4799916446208954},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4657849371433258},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4657004475593567},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.44697535037994385},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43190333247184753},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1828073263168335},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.07571977376937866}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9972623586654663},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.866820752620697},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6100866794586182},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5918685793876648},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.5275461673736572},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4799916446208954},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4657849371433258},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4657004475593567},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.44697535037994385},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43190333247184753},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1828073263168335},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07571977376937866},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3523062","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3523062","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3523062","source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3523062","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3523062","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3523062","source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.8100000023841858,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G1881860044","display_name":"SHF: Medium: Training Sparse Neural Networks with Co-Designed Hardware Accelerators: Enabling Model Optimization and Scientific Exploration","funder_award_id":"1763747","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5269767468","display_name":"CSR: Small: Deconstructing Distributed Deep Learning","funder_award_id":"1816887","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G529689006","display_name":null,"funder_award_id":"CNS-1816887","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7728769296","display_name":null,"funder_award_id":"CCF-1763747","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8787635979","display_name":null,"funder_award_id":"CNS-1816887 NSF, CCF-1763747 NSF","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4296857612.pdf","grobid_xml":"https://content.openalex.org/works/W4296857612.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1834627138","https://openalex.org/W1873763122","https://openalex.org/W1902237438","https://openalex.org/W2194321275","https://openalex.org/W2489151908","https://openalex.org/W2559840118","https://openalex.org/W2560674852","https://openalex.org/W2605800822","https://openalex.org/W2614254310","https://openalex.org/W2747329762","https://openalex.org/W2748789698","https://openalex.org/W2774423163","https://openalex.org/W2781091734","https://openalex.org/W2785509559","https://openalex.org/W2788308444","https://openalex.org/W2788629937","https://openalex.org/W2883062890","https://openalex.org/W2886444620","https://openalex.org/W2912213068","https://openalex.org/W2963334472","https://openalex.org/W2963943197","https://openalex.org/W2964043980","https://openalex.org/W2990595670","https://openalex.org/W3000479830","https://openalex.org/W3003426262","https://openalex.org/W3007358161","https://openalex.org/W3015606043","https://openalex.org/W3021654819","https://openalex.org/W3035690533","https://openalex.org/W3046449784","https://openalex.org/W3084943383","https://openalex.org/W3091870957","https://openalex.org/W3095273258","https://openalex.org/W3117572899","https://openalex.org/W3163842339","https://openalex.org/W3175919946","https://openalex.org/W3204548896","https://openalex.org/W4247950230","https://openalex.org/W4249529812","https://openalex.org/W4287550786","https://openalex.org/W4294646197","https://openalex.org/W4299828299","https://openalex.org/W4300250944","https://openalex.org/W6748263980","https://openalex.org/W6748268456","https://openalex.org/W6750254146","https://openalex.org/W6754708698","https://openalex.org/W6773039429","https://openalex.org/W6779257870","https://openalex.org/W6780292011","https://openalex.org/W6784747331"],"related_works":["https://openalex.org/W4320031223","https://openalex.org/W3015678314","https://openalex.org/W4281902577","https://openalex.org/W4200629851","https://openalex.org/W3009072493","https://openalex.org/W4386185023","https://openalex.org/W4317672133","https://openalex.org/W3127875616","https://openalex.org/W2810065831","https://openalex.org/W3128233162"],"abstract_inverted_index":{"Federated":[0],"learning":[1,98],"allows":[2],"multiple":[3],"users":[4,69],"to":[5,29,32,45,77,91,102],"collaboratively":[6],"train":[7,70],"a":[8,24,37,51,71,85,132,155],"shared":[9,43,169],"classification":[10],"model":[11,19,44,72,168],"while":[12],"preserving":[13],"data":[14],"privacy.":[15],"This":[16],"approach,":[17],"where":[18,68,140],"updates":[20],"are":[21,109,180],"aggregated":[22],"by":[23,136],"central":[25],"server,":[26],"was":[27],"shown":[28],"be":[30,75,118],"vulnerable":[31],"poisoning":[33],"backdoor":[34,62,103,178],"attacks":[35,63,104,116,179],":":[36],"malicious":[38],"user":[39],"can":[40,74,117],"alter":[41],"the":[42,59,89,141,149,163,167,171,173],"arbitrarily":[46],"classify":[47],"specific":[48],"inputs":[49],"from":[50,148,166],"given":[52],"class.":[53],"In":[54],"this":[55],"article,":[56],"we":[57,111,130],"analyze":[58],"effects":[60],"of":[61,80,143,151,158,177],"on":[64],"federated":[65,97],"meta-learning":[66],",":[67,139],"that":[73,113],"adapted":[76],"different":[78],"sets":[79],"output":[81],"classes":[82],"using":[83],"only":[84],"few":[86],"examples.":[87,160],"While":[88],"ability":[90],"adapt":[92],"could,":[93],"in":[94],"principle,":[95],"make":[96],"frameworks":[99],"more":[100],"robust":[101],"(when":[105],"new":[106],"training":[107],"examples":[108],"benign),":[110],"find":[112],"even":[114],"one-shot":[115],"very":[119],"successful":[120],"and":[121,175],"persist":[122],"after":[123],"additional":[124],"training.":[125],"To":[126],"address":[127],"these":[128],"vulnerabilities,":[129],"propose":[131],"defense":[133],"mechanism":[134],"inspired":[135],"matching":[137],"networks":[138],"class":[142],"an":[144],"input":[145],"is":[146],"predicted":[147],"similarity":[150],"its":[152],"features":[153],"with":[154,170],"support":[156],"set":[157],"labeled":[159],"By":[161],"removing":[162],"decision":[164],"logic":[165],"federation,":[172],"success":[174],"persistence":[176],"greatly":[181],"reduced.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}