{"id":"https://openalex.org/W7155381760","doi":"https://doi.org/10.48550/arxiv.2604.20596","title":"Differentially Private Clustered Federated Learning with Privacy-Preserving Initialization and Normality-Driven Aggregation","display_name":"Differentially Private Clustered Federated Learning with Privacy-Preserving Initialization and Normality-Driven Aggregation","publication_year":2026,"publication_date":"2026-04-22","ids":{"openalex":"https://openalex.org/W7155381760","doi":"https://doi.org/10.48550/arxiv.2604.20596"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.20596","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20596","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.20596","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134388041","display_name":"Jie Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xu, Jie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063935505","display_name":"Haaris Mehmood","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mehmood, Haaris","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045282611","display_name":"Rogier van Dalen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Van Dalen, Rogier","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134417143","display_name":"Karthikeyan Saravanan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saravanan, Karthikeyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134364380","display_name":"Mete Ozay","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ozay, Mete","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5134388041"],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9835000038146973,"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":0.9835000038146973,"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":0.0019000000320374966,"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/T14347","display_name":"Big Data and Digital Economy","score":0.00139999995008111,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/differential-privacy","display_name":"Differential privacy","score":0.8503000140190125},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.7677000164985657},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.5376999974250793},{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.49000000953674316},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.46549999713897705},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.4569000005722046},{"id":"https://openalex.org/keywords/artificial-noise","display_name":"Artificial noise","score":0.4133000075817108},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.3921000063419342},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.391400009393692},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.38690000772476196}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8575999736785889},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.8503000140190125},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.7677000164985657},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.5376999974250793},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.49000000953674316},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.46549999713897705},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.4569000005722046},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4146000146865845},{"id":"https://openalex.org/C2780909371","wikidata":"https://www.wikidata.org/wiki/Q4801092","display_name":"Artificial noise","level":4,"score":0.4133000075817108},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.3921000063419342},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.391400009393692},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.38690000772476196},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.38339999318122864},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.373199999332428},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.36660000681877136},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36079999804496765},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.35179999470710754},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.33550000190734863},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.3208000063896179},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3203999996185303},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.319599986076355},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C177284502","wikidata":"https://www.wikidata.org/wiki/Q1005390","display_name":"Adapter (computing)","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C2780821482","wikidata":"https://www.wikidata.org/wiki/Q25381721","display_name":"Crowdsensing","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.2759000062942505},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2651999890804291},{"id":"https://openalex.org/C164100034","wikidata":"https://www.wikidata.org/wiki/Q1870629","display_name":"Loose coupling","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.250900000333786},{"id":"https://openalex.org/C40305131","wikidata":"https://www.wikidata.org/wiki/Q2616305","display_name":"Obfuscation","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.20596","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20596","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.20596","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20596","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4927639067173004}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Federated":[0],"learning":[1,64,72],"(FL)":[2],"enables":[3],"training":[4],"of":[5,147,180,206],"a":[6,126,135,144,166],"global":[7],"model":[8],"while":[9,183],"keeping":[10],"raw":[11],"data":[12,57,85],"on":[13],"end-devices.":[14],"Despite":[15],"this,":[16],"FL":[17,182],"has":[18],"shown":[19],"to":[20,44,49,82,109,155],"leak":[21],"private":[22],"user":[23],"information":[24],"and":[25,40,67,104,141,173],"thus":[26],"in":[27,208,214],"practice,":[28],"it":[29],"is":[30,107],"often":[31],"coupled":[32],"with":[33,90,113],"methods":[34],"such":[35],"as":[36],"differential":[37],"privacy":[38,47,186,211],"(DP)":[39],"secure":[41],"vector":[42],"sum":[43],"provide":[45],"formal":[46,185],"guarantees":[48,187],"its":[50],"participants.":[51],"In":[52,160],"realistic":[53],"cross-device":[54],"deployments,":[55],"the":[56,94,105,114,148,161,178],"are":[58],"highly":[59],"heterogeneous,":[60],"so":[61],"vanilla":[62],"federated":[63,71],"converges":[65],"slowly":[66],"generalizes":[68],"poorly.":[69],"Clustered":[70],"(CFL)":[73],"mitigates":[74],"this":[75,121],"by":[76,203],"segregating":[77],"users":[78],"into":[79],"clusters,":[80],"leading":[81],"lower":[83],"intra-cluster":[84],"heterogeneity.":[86],"Nevertheless,":[87],"coupling":[88],"CFL":[89],"DP":[91,96],"remains":[92],"challenging:":[93],"injected":[95],"noise":[97],"makes":[98],"individual":[99],"client":[100,133],"updates":[101],"excessively":[102],"noisy,":[103],"server":[106,151],"unable":[108],"initialize":[110],"cluster":[111,158],"centroids":[112],"less":[115],"noisy":[116],"aggregated":[117],"updates.":[118],"To":[119],"address":[120],"challenge,":[122],"we":[123],"propose":[124],"PINA,":[125],"two-stage":[127],"framework":[128],"that":[129,170,195],"first":[130],"lets":[131],"each":[132],"fine-tune":[134],"lightweight":[136],"low-rank":[137],"adaptation":[138],"(LoRA)":[139],"adapter":[140],"privately":[142],"share":[143],"compressed":[145],"sketch":[146],"update.":[149],"The":[150],"leverages":[152],"these":[153],"sketches":[154],"construct":[156],"robust":[157],"centroids.":[159],"second":[162],"stage,":[163],"PINA":[164],"introduces":[165],"normality-driven":[167],"aggregation":[168],"mechanism":[169],"improves":[171],"convergence":[172],"robustness.":[174],"Our":[175],"method":[176,198],"retains":[177],"benefits":[179],"clustered":[181],"providing":[184],"against":[188],"an":[189,204],"untrusted":[190],"server.":[191],"Extensive":[192],"evaluations":[193],"show":[194],"our":[196],"proposed":[197],"outperforms":[199],"state-of-the-art":[200],"DP-FL":[201],"algorithms":[202],"average":[205],"2.9%":[207],"accuracy":[209],"for":[210],"budgets":[212],"(epsilon":[213],"{2,":[215],"8}).":[216]},"counts_by_year":[],"updated_date":"2026-04-24T06:07:52.864757","created_date":"2026-04-24T00:00:00"}