{"id":"https://openalex.org/W4407693818","doi":"https://doi.org/10.1109/dsit61374.2024.10881887","title":"FedHiT: Privacy Protection for Federated Learning via Hierarchical Training","display_name":"FedHiT: Privacy Protection for Federated Learning via Hierarchical Training","publication_year":2024,"publication_date":"2024-12-20","ids":{"openalex":"https://openalex.org/W4407693818","doi":"https://doi.org/10.1109/dsit61374.2024.10881887"},"language":"en","primary_location":{"id":"doi:10.1109/dsit61374.2024.10881887","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsit61374.2024.10881887","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 7th International Conference on Data Science and Information Technology (DSIT)","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/A5019146446","display_name":"Wenjie Shen","orcid":"https://orcid.org/0000-0002-3071-9556"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjie Shen","raw_affiliation_strings":["Zhejiang University of Technology,College of Information Engineering,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University of Technology,College of Information Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Guojun Sheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guojun Sheng","raw_affiliation_strings":["COSMOPlat IoT Technology Co.,Ltd.,Qingdao,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"COSMOPlat IoT Technology Co.,Ltd.,Qingdao,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101834273","display_name":"Xiaohua Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohua Pan","raw_affiliation_strings":["Binjiang Institute of Zhejiang University,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Binjiang Institute of Zhejiang University,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101758654","display_name":"Jinyin Chen","orcid":"https://orcid.org/0000-0002-7153-2755"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinyin Chen","raw_affiliation_strings":["Zhejiang University of Technology,Institute of Cyberspace Security College of Information Engineering,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University of Technology,Institute of Cyberspace Security College of Information Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100428986","display_name":"Xiaojuan Wang","orcid":"https://orcid.org/0000-0003-2195-2046"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojuan Wang","raw_affiliation_strings":["Zhejiang University of Technology,College of Information Engineering,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University of Technology,College of Information Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072212265","display_name":"Haibin Zheng","orcid":"https://orcid.org/0000-0002-8997-5343"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haibin Zheng","raw_affiliation_strings":["Zhejiang University of Technology,Institute of Cyberspace Security College of Information Engineering,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University of Technology,Institute of Cyberspace Security College of Information Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I55712492"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30892621,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9761999845504761,"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/T11614","display_name":"Cloud Data Security Solutions","score":0.9416000247001648,"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/computer-science","display_name":"Computer science","score":0.7355858087539673},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6807591915130615},{"id":"https://openalex.org/keywords/privacy-protection","display_name":"Privacy protection","score":0.6122238636016846},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.5401275753974915},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.5205622315406799},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.5123913884162903},{"id":"https://openalex.org/keywords/internet-privacy","display_name":"Internet privacy","score":0.43231523036956787},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25851863622665405}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7355858087539673},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6807591915130615},{"id":"https://openalex.org/C3017597292","wikidata":"https://www.wikidata.org/wiki/Q25052250","display_name":"Privacy protection","level":2,"score":0.6122238636016846},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5401275753974915},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.5205622315406799},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.5123913884162903},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.43231523036956787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25851863622665405},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsit61374.2024.10881887","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsit61374.2024.10881887","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 7th International Conference on Data Science and Information Technology (DSIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2068143382","https://openalex.org/W2112796928","https://openalex.org/W2535838896","https://openalex.org/W2606882085","https://openalex.org/W2979930345","https://openalex.org/W2995022099","https://openalex.org/W3016632787","https://openalex.org/W3081130510","https://openalex.org/W3118193455","https://openalex.org/W3209559250","https://openalex.org/W4205260486","https://openalex.org/W4205423013","https://openalex.org/W4213212372","https://openalex.org/W4224943538","https://openalex.org/W4284709622","https://openalex.org/W4285170881","https://openalex.org/W4295308203","https://openalex.org/W6764838729","https://openalex.org/W6773039429","https://openalex.org/W6775563089","https://openalex.org/W6780438843","https://openalex.org/W6780501606","https://openalex.org/W6784042051","https://openalex.org/W6787972765","https://openalex.org/W7005545243"],"related_works":["https://openalex.org/W2584827882","https://openalex.org/W3195097297","https://openalex.org/W3038106605","https://openalex.org/W2513267613","https://openalex.org/W3049084372","https://openalex.org/W2528109871","https://openalex.org/W2940702331","https://openalex.org/W2905822832","https://openalex.org/W4225340788","https://openalex.org/W4318485713"],"abstract_inverted_index":{"Federated":[0],"learning":[1],"(FL),":[2],"collaborating":[3],"with":[4,177,205,240],"thousands":[5],"of":[6,16,28,35,44,51,213,220,235],"participants":[7],"in":[8,71,115,190],"a":[9,33,87,106],"distributed":[10,49],"manner,":[11],"greatly":[12],"protects":[13],"the":[14,42,98,100,116,136,161,182,201,218,241],"privacy":[15,29,45,56,89,147,196,228],"local":[17],"data.":[18],"However,":[19,65],"recent":[20],"research":[21],"reveals":[22],"that":[23,185,212,234],"FL":[24,92],"is":[25,207,231],"at":[26],"risk":[27],"leakage":[30,148],"attacks.":[31],"Consequently,":[32],"variety":[34],"techniques":[36,67],"have":[37],"been":[38],"applied":[39],"to":[40,135],"address":[41,81],"issue":[43],"protection":[46,90,197,229],"and":[47,61,78,150,181,195,237],"effective":[48],"training":[50],"FL,":[52],"such":[53],"as":[54],"differential":[55],"(DP),":[57],"gradient":[58],"compression":[59],"(GC),":[60],"homomorphic":[62],"encryption":[63],"(HE).":[64],"these":[66,82],"are":[68,168],"still":[69],"limited":[70],"three":[72,117,171,174,178],"aspects,":[73],"i.e.,":[74],"communication":[75,121,126,193],"overhead,":[76,194],"fidelity,":[77],"effectiveness.":[79],"To":[80],"challenges,":[83],"we":[84],"propose":[85],"FedHiT,":[86],"novel":[88],"for":[91],"via":[93],"hierarchical":[94,107],"training.":[95],"It":[96],"minimizes":[97],"information":[99],"curious-but-honest":[101],"server":[102,137],"acquires":[103],"by":[104],"employing":[105],"upload":[108],"mechanism.":[109],"FedHiT":[110,186,206,222],"differs":[111],"from":[112],"previous":[113],"work":[114],"key":[118],"aspects:":[119],"(1)":[120],"-":[122,141,155],"it":[123,129,142,156],"has":[124],"low":[125],"overhead":[127],"since":[128],"only":[130,208,223],"uploads":[131],"partial":[132],"model":[133,191,203],"parameters":[134],"iteratively;":[138],"(2)":[139],"effectiveness":[140,158],"can":[143],"effectively":[144],"defense":[145,216],"various":[146],"attacks":[149],"adaptive":[151],"attacks;":[152],"(3)":[153],"fidelity":[154,219],"ensures":[157],"while":[159],"maintaining":[160],"model\u2019s":[162],"accuracy":[163,204],"without":[164,214],"compromise.":[165],"Extensive":[166],"experiments":[167],"conducted":[169],"on":[170],"datasets":[172],"under":[173],"attacks,":[175],"compared":[176],"state-of-the-art":[179],"baselines,":[180],"results":[183],"testify":[184],"outperforms":[187],"other":[188],"methods":[189,239],"accuracy,":[192],"capacity.":[198],"For":[199],"instance,":[200],"average":[202],"1.59%":[209],"lower":[210],"than":[211],"any":[215],"(i.e.,":[217],"using":[221],"lost":[224],"1.59%),":[225],"but":[226],"its":[227],"ability":[230],"1.4\u223c2":[232],"times":[233],"DP":[236],"GC":[238],"same":[242],"fidelity.":[243]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}