{"id":"https://openalex.org/W3138198612","doi":"https://doi.org/10.1016/j.hcc.2021.100002","title":"Towards multi-party targeted model poisoning attacks against federated learning systems","display_name":"Towards multi-party targeted model poisoning attacks against federated learning systems","publication_year":2021,"publication_date":"2021-03-23","ids":{"openalex":"https://openalex.org/W3138198612","doi":"https://doi.org/10.1016/j.hcc.2021.100002","mag":"3138198612"},"language":"en","primary_location":{"id":"doi:10.1016/j.hcc.2021.100002","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.hcc.2021.100002","pdf_url":"https://www.sciencedirect.com/science/article/pii/S2667295221000039/pdf","source":{"id":"https://openalex.org/S4210186527","display_name":"High-Confidence Computing","issn_l":"2667-2952","issn":["2667-2952"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"High-Confidence Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.sciencedirect.com/science/article/pii/S2667295221000039/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102732574","display_name":"Zheyi Chen","orcid":"https://orcid.org/0009-0003-9631-2921"},"institutions":[{"id":"https://openalex.org/I4322298","display_name":"Towson University","ror":"https://ror.org/044w7a341","country_code":"US","type":"education","lineage":["https://openalex.org/I4322298"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zheyi Chen","raw_affiliation_strings":["Department of Computer and Information Sciences, Towson University, MD 21252 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, Towson University, MD 21252 USA","institution_ids":["https://openalex.org/I4322298"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103074653","display_name":"Tian Pu","orcid":"https://orcid.org/0000-0002-5150-8053"},"institutions":[{"id":"https://openalex.org/I4322298","display_name":"Towson University","ror":"https://ror.org/044w7a341","country_code":"US","type":"education","lineage":["https://openalex.org/I4322298"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pu Tian","raw_affiliation_strings":["Department of Computer and Information Sciences, Towson University, MD 21252 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, Towson University, MD 21252 USA","institution_ids":["https://openalex.org/I4322298"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083406034","display_name":"Weixian Liao","orcid":"https://orcid.org/0000-0003-1444-8925"},"institutions":[{"id":"https://openalex.org/I4322298","display_name":"Towson University","ror":"https://ror.org/044w7a341","country_code":"US","type":"education","lineage":["https://openalex.org/I4322298"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Weixian Liao","raw_affiliation_strings":["Department of Computer and Information Sciences, Towson University, MD 21252 USA"],"raw_orcid":"https://orcid.org/0000-0003-1444-8925","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, Towson University, MD 21252 USA","institution_ids":["https://openalex.org/I4322298"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002139930","display_name":"Wei Yu","orcid":"https://orcid.org/0000-0003-4522-7340"},"institutions":[{"id":"https://openalex.org/I4322298","display_name":"Towson University","ror":"https://ror.org/044w7a341","country_code":"US","type":"education","lineage":["https://openalex.org/I4322298"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Yu","raw_affiliation_strings":["Department of Computer and Information Sciences, Towson University, MD 21252 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, Towson University, MD 21252 USA","institution_ids":["https://openalex.org/I4322298"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5083406034"],"corresponding_institution_ids":["https://openalex.org/I4322298"],"apc_list":{"value":1500,"currency":"USD","value_usd":1500},"apc_paid":{"value":1500,"currency":"USD","value_usd":1500},"fwci":2.8663,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.91973257,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"1","issue":"1","first_page":"100002","last_page":"100002"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9850000143051147,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9624000191688538,"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/computer-science","display_name":"Computer science","score":0.8156870007514954},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.767906129360199},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.670361340045929},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.6253806948661804},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5176749229431152},{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.5119324922561646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2895117402076721}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8156870007514954},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.767906129360199},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.670361340045929},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.6253806948661804},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5176749229431152},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.5119324922561646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2895117402076721}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.hcc.2021.100002","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.hcc.2021.100002","pdf_url":"https://www.sciencedirect.com/science/article/pii/S2667295221000039/pdf","source":{"id":"https://openalex.org/S4210186527","display_name":"High-Confidence Computing","issn_l":"2667-2952","issn":["2667-2952"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"High-Confidence Computing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c629ac91e25c43d0baf0b8141e6585a7","is_oa":true,"landing_page_url":"https://doaj.org/article/c629ac91e25c43d0baf0b8141e6585a7","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"High-Confidence Computing, Vol 1, Iss 1, Pp 100002- (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1016/j.hcc.2021.100002","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.hcc.2021.100002","pdf_url":"https://www.sciencedirect.com/science/article/pii/S2667295221000039/pdf","source":{"id":"https://openalex.org/S4210186527","display_name":"High-Confidence Computing","issn_l":"2667-2952","issn":["2667-2952"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"High-Confidence Computing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3138198612.pdf","grobid_xml":"https://content.openalex.org/works/W3138198612.grobid-xml"},"referenced_works_count":102,"referenced_works":["https://openalex.org/W1502957213","https://openalex.org/W2095705004","https://openalex.org/W2098897917","https://openalex.org/W2106267320","https://openalex.org/W2124861999","https://openalex.org/W2125908420","https://openalex.org/W2167421362","https://openalex.org/W2180612164","https://openalex.org/W2460937040","https://openalex.org/W2535838896","https://openalex.org/W2541884796","https://openalex.org/W2557044351","https://openalex.org/W2596636257","https://openalex.org/W2604738573","https://openalex.org/W2612690371","https://openalex.org/W2738015883","https://openalex.org/W2750650104","https://openalex.org/W2752689052","https://openalex.org/W2753783305","https://openalex.org/W2774423163","https://openalex.org/W2783097478","https://openalex.org/W2786070938","https://openalex.org/W2788816110","https://openalex.org/W2789903762","https://openalex.org/W2789911054","https://openalex.org/W2790400697","https://openalex.org/W2791218785","https://openalex.org/W2794878842","https://openalex.org/W2800017313","https://openalex.org/W2803678876","https://openalex.org/W2805258854","https://openalex.org/W2810065831","https://openalex.org/W2888233014","https://openalex.org/W2902264868","https://openalex.org/W2912213068","https://openalex.org/W2913452160","https://openalex.org/W2913668833","https://openalex.org/W2922822742","https://openalex.org/W2946633206","https://openalex.org/W2948502305","https://openalex.org/W2949506549","https://openalex.org/W2949522309","https://openalex.org/W2950447132","https://openalex.org/W2959053776","https://openalex.org/W2963068442","https://openalex.org/W2963165390","https://openalex.org/W2963178695","https://openalex.org/W2963422767","https://openalex.org/W2963495269","https://openalex.org/W2964043980","https://openalex.org/W2964248614","https://openalex.org/W2964283260","https://openalex.org/W2966059442","https://openalex.org/W2978648093","https://openalex.org/W2982407593","https://openalex.org/W2990138404","https://openalex.org/W3002416713","https://openalex.org/W3010058322","https://openalex.org/W3012539654","https://openalex.org/W3035498193","https://openalex.org/W3036791758","https://openalex.org/W3042029390","https://openalex.org/W3046449784","https://openalex.org/W3103822831","https://openalex.org/W4230858134","https://openalex.org/W4236550001","https://openalex.org/W4236965008","https://openalex.org/W4241109792","https://openalex.org/W4288414371","https://openalex.org/W4288647574","https://openalex.org/W4365806382","https://openalex.org/W6674330103","https://openalex.org/W6676935882","https://openalex.org/W6684559340","https://openalex.org/W6685736903","https://openalex.org/W6719080892","https://openalex.org/W6728757088","https://openalex.org/W6729007826","https://openalex.org/W6730054736","https://openalex.org/W6741570309","https://openalex.org/W6743821447","https://openalex.org/W6746188276","https://openalex.org/W6746897123","https://openalex.org/W6748110298","https://openalex.org/W6748626757","https://openalex.org/W6748786018","https://openalex.org/W6750023670","https://openalex.org/W6751569023","https://openalex.org/W6752429284","https://openalex.org/W6752600739","https://openalex.org/W6756840679","https://openalex.org/W6758201434","https://openalex.org/W6760425369","https://openalex.org/W6762462524","https://openalex.org/W6763817913","https://openalex.org/W6765502031","https://openalex.org/W6769746359","https://openalex.org/W6771941255","https://openalex.org/W6773235137","https://openalex.org/W6780452058","https://openalex.org/W6780479830","https://openalex.org/W6785689674"],"related_works":["https://openalex.org/W4320018150","https://openalex.org/W2040808657","https://openalex.org/W2918664383","https://openalex.org/W4320855730","https://openalex.org/W106056076","https://openalex.org/W2135200719","https://openalex.org/W4387985143","https://openalex.org/W4362599004","https://openalex.org/W2808242528","https://openalex.org/W1567638270"],"abstract_inverted_index":{"The":[0],"federated":[1,42,213],"learning":[2,7,51,214],"framework":[3],"builds":[4],"a":[5,11,87,104,151],"deep":[6],"model":[8,112,138,194],"collaboratively":[9,109],"by":[10,101,155],"group":[12],"of":[13,30,96,106,137,179,208],"connected":[14],"devices":[15,108,131],"via":[16],"only":[17],"sharing":[18],"local":[19,34],"parameter":[20,25],"updates":[21],"to":[22,40,49,116],"the":[23,28,33,59,72,93,97,118,129,134,145,174,186,192,196,200,205,209],"central":[24],"server.":[26],"Nonetheless,":[27],"lack":[29],"transparency":[31],"in":[32,140],"data":[35],"resource":[36],"makes":[37],"it":[38],"prone":[39],"adversarial":[41,90],"attacks,":[43,114],"which":[44,203],"have":[45],"shown":[46],"increasing":[47],"ability":[48,70],"reduce":[50],"performance.":[52],"Existing":[53],"research":[54],"efforts":[55],"either":[56],"focus":[57],"on":[58,79,199,212],"single-party":[60],"attack":[61,74,80,91,176,211],"with":[62,92],"impractical":[63],"perfect":[64,168],"knowledge":[65,95,169,172],"setting":[66],"and":[67,170],"limited":[68,171],"stealthy":[69,123,158],"or":[71],"random":[73],"that":[75,165,191],"has":[76],"no":[77],"control":[78],"effects.":[81],"In":[82],"this":[83],"paper,":[84],"we":[85,149,163],"investigate":[86],"new":[88,152],"multi-party":[89,175,210],"imperfect":[94],"target":[98],"system.":[99],"Controlled":[100],"an":[102],"adversary,":[103],"number":[105],"compromised":[107,130],"launch":[110],"targeted":[111,119,201],"poisoning":[113],"intending":[115],"misclassify":[117],"samples":[120],"while":[121,184],"maintaining":[122],"under":[124,166],"different":[125,141],"detection":[126,182],"strategies.":[127],"Specifically,":[128],"jointly":[132],"minimize":[133],"loss":[135],"function":[136],"training":[139],"scenarios.":[142],"To":[143],"overcome":[144],"update":[146],"scaling":[147],"problem,":[148],"develop":[150],"boosting":[153],"strategy":[154],"introducing":[156],"two":[157],"metrics.":[159],"Via":[160],"experimental":[161],"results,":[162],"show":[164],"both":[167],"settings,":[173],"is":[177],"capable":[178],"successfully":[180],"evading":[181],"strategies":[183],"guaranteeing":[185],"convergence.":[187],"We":[188],"also":[189],"demonstrate":[190],"learned":[193],"achieves":[195],"high":[197],"accuracy":[198],"samples,":[202],"confirms":[204],"significant":[206],"impact":[207],"systems.":[215]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2026-08-02T14:50:37.381335","created_date":"2025-10-10T00:00:00"}