{"id":"https://openalex.org/W4415708603","doi":"https://doi.org/10.1109/icme59968.2025.11209583","title":"Fed3D: Enhancing Security in Federated Learning with Dataset Distillation","display_name":"Fed3D: Enhancing Security in Federated Learning with Dataset Distillation","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415708603","doi":"https://doi.org/10.1109/icme59968.2025.11209583"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11209583","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209583","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"},"type":"article","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/A5102625086","display_name":"Canhui Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Canhui Wu","raw_affiliation_strings":["Xi&#x2019;an Jiaotong University,Faculty of Electronic and Information Engineering,Xi&#x2019;an,China"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Jiaotong University,Faculty of Electronic and Information Engineering,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050052141","display_name":"Wei Xi","orcid":"https://orcid.org/0000-0001-9348-2982"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Xi","raw_affiliation_strings":["Xi&#x2019;an Jiaotong University,Faculty of Electronic and Information Engineering,Xi&#x2019;an,China"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Jiaotong University,Faculty of Electronic and Information Engineering,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100346640","display_name":"Yuwei Fan","orcid":"https://orcid.org/0009-0004-3379-2371"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuwei Fan","raw_affiliation_strings":["Xi&#x2019;an Jiaotong University,Faculty of Electronic and Information Engineering,Xi&#x2019;an,China"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Jiaotong University,Faculty of Electronic and Information Engineering,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103889970","display_name":"Yuhao Shen","orcid":"https://orcid.org/0009-0007-4097-7827"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhao Shen","raw_affiliation_strings":["Xi&#x2019;an Jiaotong University,Faculty of Electronic and Information Engineering,Xi&#x2019;an,China"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Jiaotong University,Faculty of Electronic and Information Engineering,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101471775","display_name":"Jizhong Zhao","orcid":"https://orcid.org/0000-0002-6520-8238"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jizhong Zhao","raw_affiliation_strings":["Xi&#x2019;an Jiaotong University,Faculty of Electronic and Information Engineering,Xi&#x2019;an,China"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Jiaotong University,Faculty of Electronic and Information Engineering,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102625086"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1753857,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.6227999925613403,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.6227999925613403,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.29170000553131104,"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":0.008500000461935997,"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/backdoor","display_name":"Backdoor","score":0.9563999772071838},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6717000007629395},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6455000042915344},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.6252999901771545},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48820000886917114},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.38600000739097595}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9563999772071838},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7968000173568726},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6717000007629395},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6455000042915344},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.6252999901771545},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48820000886917114},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46790000796318054},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41609999537467957},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3928999900817871},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.38600000739097595},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.32429999113082886},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.31540000438690186},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.3077000081539154},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.26080000400543213},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11209583","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209583","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W4312252393","https://openalex.org/W4312412605","https://openalex.org/W4319300193","https://openalex.org/W4324007138","https://openalex.org/W4386065613","https://openalex.org/W4390691907","https://openalex.org/W4402351499"],"related_works":[],"abstract_inverted_index":{"Dataset":[0],"Distillation":[1],"(DD)":[2],"compresses":[3],"large":[4],"datasets":[5,22,109],"into":[6,33],"compact":[7],"representations":[8],"while":[9,103],"preserving":[10],"performance,":[11],"offering":[12],"substantial":[13],"benefits":[14],"for":[15,72,121],"Federated":[16,50],"Learning":[17,51],"(FL).":[18],"However,":[19],"using":[20],"distilled":[21,35,108],"introduces":[23],"new":[24],"security":[25],"vulnerabilities,":[26],"as":[27,115],"adversaries":[28],"can":[29],"easily":[30],"embed":[31],"backdoors":[32],"the":[34,49,66,105],"data.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40,63],"extend":[41],"existing":[42],"backdoor":[43,123],"attack":[44,99],"strategies":[45],"in":[46,125],"DD":[47],"to":[48],"context":[52],"(DD-FL)":[53],"and":[54,118],"empirically":[55],"demonstrate":[56],"their":[57],"effectiveness.":[58],"To":[59],"address":[60],"these":[61],"threats,":[62],"propose":[64],"Fed3D,":[65],"first":[67],"defense":[68,78],"algorithm":[69],"specifically":[70],"designed":[71],"DD-FL.":[73],"Fed3D":[74,96,114],"incorporates":[75],"a":[76,116],"dual-layer":[77],"mechanism,":[79],"combining":[80],"intra-client":[81],"diversity":[82],"detection":[83],"with":[84],"inter-client":[85],"clustering":[86],"based":[87],"on":[88],"reconstructed":[89],"feature":[90],"representations.":[91],"Comprehensive":[92],"experiments":[93],"show":[94],"that":[95],"effectively":[97],"reduces":[98],"success":[100],"rates":[101],"(<1.5%)":[102],"maintaining":[104],"performance":[106],"of":[107],"(<1.1%).":[110],"These":[111],"results":[112],"establish":[113],"robust":[117],"promising":[119],"solution":[120],"mitigating":[122],"attacks":[124],"DD-FL":[126],"systems.":[127]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-30T00:00:00"}
