{"id":"https://openalex.org/W4401331601","doi":"https://doi.org/10.1109/fuzz-ieee60900.2024.10611846","title":"DQFed: A Federated Learning Strategy for Non-IID Data based on a Quality-Driven Perspective","display_name":"DQFed: A Federated Learning Strategy for Non-IID Data based on a Quality-Driven Perspective","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4401331601","doi":"https://doi.org/10.1109/fuzz-ieee60900.2024.10611846"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee60900.2024.10611846","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee60900.2024.10611846","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","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/A5032066141","display_name":"Mario Luca Bernardi","orcid":"https://orcid.org/0000-0002-3223-7032"},"institutions":[{"id":"https://openalex.org/I16337185","display_name":"University of Sannio","ror":"https://ror.org/04vc81p87","country_code":"IT","type":"education","lineage":["https://openalex.org/I16337185"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Mario Luca Bernardi","raw_affiliation_strings":["University of Sannio,Dept. of Engineering,Benevento,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Sannio,Dept. of Engineering,Benevento,Italy","institution_ids":["https://openalex.org/I16337185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027577443","display_name":"Marta Cimitile","orcid":"https://orcid.org/0000-0003-2403-8313"},"institutions":[{"id":"https://openalex.org/I4210130905","display_name":"Unitelma Sapienza University","ror":"https://ror.org/04dfrdm61","country_code":"IT","type":"education","lineage":["https://openalex.org/I4210130905"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Marta Cimitile","raw_affiliation_strings":["UnitelmaSapienza University,Dept. of Law and Digital Society,Rome,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UnitelmaSapienza University,Dept. of Law and Digital Society,Rome,Italy","institution_ids":["https://openalex.org/I4210130905"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014572558","display_name":"Muhammad Usman","orcid":"https://orcid.org/0000-0002-7818-4546"},"institutions":[{"id":"https://openalex.org/I16337185","display_name":"University of Sannio","ror":"https://ror.org/04vc81p87","country_code":"IT","type":"education","lineage":["https://openalex.org/I16337185"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Muhammad Usman","raw_affiliation_strings":["University of Sannio,Dept. of Engineering,Benevento,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Sannio,Dept. of Engineering,Benevento,Italy","institution_ids":["https://openalex.org/I16337185"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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":1.0,"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":0.9908000230789185,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7403072714805603},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.7355648279190063},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.596172571182251},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.41285213828086853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3064291477203369},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.14948409795761108},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.07221972942352295}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7403072714805603},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.7355648279190063},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.596172571182251},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.41285213828086853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3064291477203369},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.14948409795761108},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.07221972942352295},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz-ieee60900.2024.10611846","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee60900.2024.10611846","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2116612304","https://openalex.org/W2614183994","https://openalex.org/W2744999500","https://openalex.org/W2767106145","https://openalex.org/W2789911054","https://openalex.org/W2807006176","https://openalex.org/W2808102641","https://openalex.org/W2904760378","https://openalex.org/W2912592113","https://openalex.org/W2955213239","https://openalex.org/W2972570881","https://openalex.org/W2972882814","https://openalex.org/W2978725006","https://openalex.org/W2997590552","https://openalex.org/W3033511014","https://openalex.org/W3034321207","https://openalex.org/W3047304572","https://openalex.org/W3090393599","https://openalex.org/W3119097978","https://openalex.org/W3119526232","https://openalex.org/W3184596548","https://openalex.org/W3196371845","https://openalex.org/W3209696639","https://openalex.org/W4226376129","https://openalex.org/W4287024370","https://openalex.org/W4297687186","https://openalex.org/W4378978494","https://openalex.org/W4385800737","https://openalex.org/W4390664592","https://openalex.org/W6737563499","https://openalex.org/W6738383168","https://openalex.org/W6752029299","https://openalex.org/W6757292943","https://openalex.org/W6767676916","https://openalex.org/W6768537144"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2149537132","https://openalex.org/W2376932109","https://openalex.org/W2018871932"],"abstract_inverted_index":{"The":[0,134,163,184],"increasing":[1],"amount":[2,10],"of":[3,11,78,82,125,141],"available":[4],"smart":[5],"objects":[6],"produces":[7],"a":[8,25,36,43,49,79,111,131,181],"huge":[9,80],"data":[12,67],"that":[13,117,138,159],"can":[14,145],"be":[15,146],"successfully":[16,55],"managed":[17],"using":[18],"Federated":[19],"Learning":[20],"(FL)":[21],"approaches.":[22],"FL":[23,71,103,113],"is":[24,137,166],"distributed":[26],"deep":[27],"learning":[28],"framework":[29],"where":[30],"several":[31,58],"devices":[32],"are":[33,54,176],"trained":[34],"with":[35],"local":[37,40,120],"model":[38,144],"on":[39,122,168],"data,":[41],"and":[42,63,98,173,198],"central":[44],"server":[45],"aggregates":[46,118],"them":[47],"in":[48,57,66,76,92],"global":[50],"model.":[51,133],"These":[52],"strategies":[53,72,104],"used":[56],"contexts":[59],"ensuring":[60],"privacy":[61],"preservation":[62],"high":[64],"effectiveness":[65],"analysis.":[68],"However,":[69],"the":[70,93,119,123,139,142,150,157,192],"show":[73,186],"variable":[74],"accuracy":[75],"case":[77],"presence":[81],"non-independent-and-identically-distributed":[83],"(Non-IID)":[84],"data.":[85,107,162,200],"This":[86,108],"challenge":[87],"has":[88],"been":[89],"largely":[90],"explored":[91],"last":[94],"years":[95],"by":[96,148],"researchers":[97],"developers":[99],"who":[100],"propose":[101],"new":[102],"for":[105,195],"non-IID":[106,172,197],"study":[109],"introduces":[110],"novel":[112],"approach,":[114],"called":[115],"DQFed,":[116],"models":[121,152],"base":[124],"their":[126],"weights":[127],"computed":[128],"according":[129],"to":[130,156,191],"quality-driven":[132],"surrounding":[135],"idea":[136],"performance":[140],"general":[143],"improved":[147,188],"aggregating":[149],"clients'":[151],"giving":[153],"higher":[154],"importance":[155],"clients":[158],"use":[160],"high-quality":[161],"DQFed":[164],"strategy":[165],"evaluated":[167],"five":[169],"datasets":[170,175],"(both":[171],"IID":[174,199],"considered)":[177],"obtained":[178],"starting":[179],"from":[180],"real":[182],"dataset.":[183],"results":[185],"an":[187],"F1-score":[189],"compared":[190],"considered":[193],"baseline":[194],"both":[196]},"counts_by_year":[{"year":2025,"cited_by_count":6}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
