{"id":"https://openalex.org/W7160274286","doi":"https://doi.org/10.1109/wacv61042.2026.00667","title":"SD-CSFL: A Synthetic Data-Driven Conformity Scoring Framework for Robust Federated Learning","display_name":"SD-CSFL: A Synthetic Data-Driven Conformity Scoring Framework for Robust Federated Learning","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7160274286","doi":"https://doi.org/10.1109/wacv61042.2026.00667"},"language":null,"primary_location":{"id":"doi:10.1109/wacv61042.2026.00667","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103152926","display_name":"Ebtisaam Alharbi","orcid":"https://orcid.org/0000-0002-3969-3209"},"institutions":[{"id":"https://openalex.org/I199693650","display_name":"Umm al-Qura University","ror":"https://ror.org/01xjqrm90","country_code":"SA","type":"education","lineage":["https://openalex.org/I199693650"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Ebtisaam Alharbi","raw_affiliation_strings":["Umm Al-Qura University,Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Umm Al-Qura University,Saudi Arabia","institution_ids":["https://openalex.org/I199693650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067157654","display_name":"Abdulrahman Kerim","orcid":"https://orcid.org/0000-0003-0141-9543"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Abdulrahman Kerim","raw_affiliation_strings":["University of Surrey,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Surrey,United Kingdom","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135411837","display_name":"Leandro Soriano Marcolino","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142044","display_name":"VinUniversity","ror":"https://ror.org/052dmdr17","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210142044"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Leandro Soriano Marcolino","raw_affiliation_strings":["VinUniversity,Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VinUniversity,Vietnam","institution_ids":["https://openalex.org/I4210142044"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5135369344","display_name":"Qiang Ni","orcid":null},"institutions":[{"id":"https://openalex.org/I67415387","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36","country_code":"GB","type":"education","lineage":["https://openalex.org/I67415387"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Qiang Ni","raw_affiliation_strings":["Lancaster University,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lancaster University,United Kingdom","institution_ids":["https://openalex.org/I67415387"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"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":"6903","last_page":"6912"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.8633000254631042,"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":0.8633000254631042,"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":0.028200000524520874,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.017400000244379044,"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/conformity","display_name":"Conformity","score":0.3449000120162964},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.3188000023365021},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.3046000003814697},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.302700012922287},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.30079999566078186}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6718000173568726},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4092999994754791},{"id":"https://openalex.org/C142172996","wikidata":"https://www.wikidata.org/wiki/Q221284","display_name":"Conformity","level":2,"score":0.3449000120162964},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3310000002384186},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3188000023365021},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.302700012922287},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.2526000142097473},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv61042.2026.00667","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311687","display_name":"Ministry of Education","ror":"https://ror.org/03m01yf64"},{"id":"https://openalex.org/F4320318570","display_name":"Saudi Arabian Cultural Bureau","ror":null},{"id":"https://openalex.org/F4320324047","display_name":"Umm Al-Qura University","ror":"https://ror.org/01xjqrm90"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W3138597937","https://openalex.org/W3175919946","https://openalex.org/W4206320562","https://openalex.org/W4213446860","https://openalex.org/W4312933868","https://openalex.org/W4366966548","https://openalex.org/W4382237486","https://openalex.org/W4382469137","https://openalex.org/W4387185306","https://openalex.org/W4399671137","https://openalex.org/W4410609084","https://openalex.org/W7133229619"],"related_works":[],"abstract_inverted_index":{"Federated":[0,55],"Learning":[1],"(FL)":[2],"enables":[3],"collaborative":[4],"model":[5],"training":[6,99],"without":[7],"sharing":[8],"raw":[9],"data,":[10,39,72],"but":[11],"remains":[12],"highly":[13],"vulnerable":[14],"to":[15,42,73,125],"gradient":[16,130],"manipulation":[17,131],"and":[18,59,121,132,148],"backdoor":[19,137],"attacks,":[20,35],"particularly":[21],"under":[22,114],"heterogeneous":[23,45,144],"client":[24,38,71,82],"distributions.":[25,117],"Most":[26],"existing":[27],"defenses":[28,142],"either":[29],"target":[30],"a":[31,57,65,103],"narrow":[32],"class":[33],"of":[34,70,129],"rely":[36],"on":[37,119],"or":[40],"fail":[41],"adapt":[43],"in":[44,81,136,143],"settings.":[46],"We":[47,101],"propose":[48],"SD-CSFL":[49,63],"(Synthetic":[50],"Data-Driven":[51],"Conformity":[52],"Scoring":[53],"for":[54],"Learning),":[56],"unified":[58],"privacy-preserving":[60],"defense":[61],"algorithm.":[62],"leverages":[64],"synthetic":[66,149],"calibration":[67,91],"dataset,":[68],"independent":[69],"compute":[74],"entropy-based":[75],"nonconformity":[76],"scores":[77],"that":[78,108],"capture":[79],"irregularities":[80],"updates.":[83],"An":[84],"adaptive":[85],"percentile":[86,109],"thresholding":[87],"mechanism":[88],"with":[89],"stratified":[90],"dynamically":[92],"distinguishes":[93],"benign":[94],"from":[95],"malicious":[96],"updates":[97],"across":[98],"rounds.":[100],"establish":[102],"conformal":[104],"prediction-based":[105],"guarantee":[106],"showing":[107],"thresholds":[110],"bound":[111],"false":[112],"positives":[113],"arbitrary":[115],"score":[116],"Experiments":[118],"CIFAR-10":[120],"Birds-525":[122],"demonstrate":[123],"up":[124],"35%":[126],"higher":[127],"detection":[128],"an":[133],"80%":[134],"reduction":[135],"success":[138],"rates,":[139],"outperforming":[140],"recent":[141],"environments.":[145],"Our":[146],"implementations":[147],"datasets":[150],"are":[151],"available":[152],"at":[153],"https://github.com/EbtisaamCS/SD-CSFL":[154]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-05-06T00:00:00"}