{"id":"https://openalex.org/W7125937348","doi":"https://doi.org/10.1109/icait66450.2025.11353293","title":"FLNAP: Mitigating LDP Impact in Federated Learning with Noise-Aware Pre-Training","display_name":"FLNAP: Mitigating LDP Impact in Federated Learning with Noise-Aware Pre-Training","publication_year":2025,"publication_date":"2025-10-24","ids":{"openalex":"https://openalex.org/W7125937348","doi":"https://doi.org/10.1109/icait66450.2025.11353293"},"language":"en","primary_location":{"id":"doi:10.1109/icait66450.2025.11353293","doi":"https://doi.org/10.1109/icait66450.2025.11353293","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icait66450.2025.11353293","pdf_url":null,"source":{"id":"https://openalex.org/S4306418645","display_name":"IEEE International Conference on Advanced Infocomm Technology","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 17th International Conference on Advanced Infocomm Technology (ICAIT)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5063748382","display_name":"Qingkui Zeng","orcid":"https://orcid.org/0000-0002-4984-4955","observed_orcids":["https://orcid.org/0000-0002-4984-4955","https://orcid.org/0000-0002-1683-7441"]},"institutions":[{"id":"https://openalex.org/I4210159152","display_name":"Tongling University","ror":"https://ror.org/04kqvjg13","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210159152"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingkui Zeng","raw_affiliation_strings":["Tongling University,School of Mathematics and Computer Science,Tongling,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tongling University,School of Mathematics and Computer Science,Tongling,China","institution_ids":["https://openalex.org/I4210159152"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072315579","display_name":"Zhuotao Lian","orcid":"https://orcid.org/0000-0003-2938-6368","observed_orcids":["https://orcid.org/0000-0003-2938-6368"]},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zhuotao Lian","raw_affiliation_strings":["Hiroshima University,Graduate School of Advanced Science and Engineering,Higashi-Hiroshima,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hiroshima University,Graduate School of Advanced Science and Engineering,Higashi-Hiroshima,Japan","institution_ids":["https://openalex.org/I113306721"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109946334","display_name":"Heling Niu","orcid":"https://orcid.org/0009-0009-1021-4495","observed_orcids":["https://orcid.org/0009-0009-1021-4495"]},"institutions":[{"id":"https://openalex.org/I196934937","display_name":"Liaocheng University","ror":"https://ror.org/03yh0n709","country_code":"CN","type":"education","lineage":["https://openalex.org/I196934937"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huijuan Niu","raw_affiliation_strings":["Liaocheng University,School of Physics Science and Information Technology,Liaocheng,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Liaocheng University,School of Physics Science and Information Technology,Liaocheng,China","institution_ids":["https://openalex.org/I196934937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029072107","display_name":"Jingcheng Song","orcid":"https://orcid.org/0000-0002-8297-3492","observed_orcids":["https://orcid.org/0000-0002-8297-3492"]},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingcheng Song","raw_affiliation_strings":["Linyi University,School of Information Science and Engineering,Linyi,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Linyi University,School of Information Science and Engineering,Linyi,China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124092722","display_name":"Hong Zhao","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I135714990","display_name":"North University of China","ror":"https://ror.org/047bp1713","country_code":"CN","type":"education","lineage":["https://openalex.org/I135714990"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Zhao","raw_affiliation_strings":["North University of China,School of Computer Science and Engineering,Taiyuan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North University of China,School of Computer Science and Engineering,Taiyuan,China","institution_ids":["https://openalex.org/I135714990"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003950500","display_name":"Chunhua Su","orcid":"https://orcid.org/0000-0002-6461-9684","observed_orcids":["https://orcid.org/0000-0002-6461-9684"]},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chunhua Su","raw_affiliation_strings":["University of Aizu,School of Computer Science and Engineering,Aizuwakamatsu,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Aizu,School of Computer Science and Engineering,Aizuwakamatsu,Japan","institution_ids":["https://openalex.org/I141591182"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6456,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.75445316,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":92,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"128","last_page":"134"},"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.0,"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":0.0,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/federated-learning","display_name":"federated learning","score":0.9919999837875366},{"id":"https://openalex.org/keywords/local-differential-privacy","display_name":"local differential privacy","score":0.9980000257492065},{"id":"https://openalex.org/keywords/privacy-utility-trade-off","display_name":"privacy-utility trade-off","score":0.8199999928474426},{"id":"https://openalex.org/keywords/communication-efficiency","display_name":"communication efficiency","score":0.9940000176429749},{"id":"https://openalex.org/keywords/privacy-preserving-machine-learning","display_name":"privacy-preserving machine learning","score":0.5680000185966492}],"concepts":[{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.8260999917984009},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.8242999911308289},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8036999702453613},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.7056999802589417},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5712000131607056},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.5532000064849854},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.4462999999523163},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4025999903678894},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.3846000134944916},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.33219999074935913},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.287200003862381},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.28060001134872437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27869999408721924},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.27730000019073486},{"id":"https://openalex.org/C67363961","wikidata":"https://www.wikidata.org/wiki/Q5268834","display_name":"Information and Communications Technology","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.26440000534057617},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2556000053882599},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icait66450.2025.11353293","doi":"https://doi.org/10.1109/icait66450.2025.11353293","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icait66450.2025.11353293","pdf_url":null,"source":{"id":"https://openalex.org/S4306418645","display_name":"IEEE International Conference on Advanced Infocomm Technology","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 17th International Conference on Advanced Infocomm Technology (ICAIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2112796928","https://openalex.org/W2342135826","https://openalex.org/W2473418344","https://openalex.org/W2781091734","https://openalex.org/W2964162474","https://openalex.org/W3027176637","https://openalex.org/W3090107331","https://openalex.org/W3094542121","https://openalex.org/W3192324887","https://openalex.org/W3192796768","https://openalex.org/W4214607237","https://openalex.org/W4287691174","https://openalex.org/W4380091325","https://openalex.org/W4387503881","https://openalex.org/W4391341820","https://openalex.org/W4391620743","https://openalex.org/W4399938968","https://openalex.org/W4401937295","https://openalex.org/W4402265834","https://openalex.org/W4404952658","https://openalex.org/W4406047340"],"related_works":["https://openalex.org/W7160767474","https://openalex.org/W7204556998","https://openalex.org/W4393372120","https://openalex.org/W4328028544","https://openalex.org/W7118670497","https://openalex.org/W4405707066","https://openalex.org/W7130181458","https://openalex.org/W7128991557","https://openalex.org/W4412598586","https://openalex.org/W7163586703"],"abstract_inverted_index":{"Federated":[0],"Learning":[1],"(FL)":[2],"preserves":[3],"data":[4],"privacy":[5,54,62],"by":[6],"training":[7],"models":[8],"locally,":[9],"but":[10],"Local":[11],"Differential":[12],"Privacy":[13],"(LDP)":[14],"schemes":[15],"often":[16],"degrade":[17],"convergence":[18,66,84,98],"and":[19,70,83,100],"communication":[20,72,101],"efficiency.":[21],"To":[22],"address":[23],"this,":[24],"we":[25],"propose":[26],"FLNAP,":[27],"a":[28],"novel":[29],"LDPenabled":[30],"FL":[31],"framework":[32],"that":[33,94],"leverages":[34],"global":[35],"model":[36,49],"pre-training":[37],"with":[38],"noise-integration.":[39],"Unlike":[40],"existing":[41],"methods":[42],"requiring":[43],"trusted":[44],"curators,":[45],"our":[46,95],"approach":[47,96],"perturbs":[48],"updates":[50],"during":[51],"pretraining,":[52],"decoupling":[53],"injection":[55],"from":[56],"federated":[57],"rounds.":[58],"This":[59],"achieves":[60],"stronger":[61],"guarantees,":[63],"significantly":[64],"improves":[65,97],"resilience":[67],"to":[68],"noise,":[69],"reduces":[71],"overhead.":[73],"We":[74],"provide":[75],"rigorous":[76],"theoretical":[77],"analysis":[78],"of":[79],"the":[80],"privacyutility":[81],"tradeoff":[82],"guarantees.":[85],"Extensive":[86],"experiments":[87],"on":[88],"benchmark":[89],"datasets":[90],"(MNIST,":[91],"CIFAR-10)":[92],"demonstrate":[93],"performance":[99],"efficiency":[102],"while":[103],"providing":[104],"privacy-preserving":[105,114],"capabilities.":[106],"Index":[107],"Terms-federated":[108],"learning,":[109],"local":[110],"differential":[111],"privacy,":[112],"pre-training,":[113]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-01-29T00:00:00"}