{"id":"https://openalex.org/W4410229650","doi":"https://doi.org/10.1109/iccae64891.2025.10980580","title":"Security Evaluation of Differentially Private Federated Learning Against Model Inversion Attacks","display_name":"Security Evaluation of Differentially Private Federated Learning Against Model Inversion Attacks","publication_year":2025,"publication_date":"2025-03-20","ids":{"openalex":"https://openalex.org/W4410229650","doi":"https://doi.org/10.1109/iccae64891.2025.10980580"},"language":"en","primary_location":{"id":"doi:10.1109/iccae64891.2025.10980580","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccae64891.2025.10980580","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 17th International Conference on Computer and Automation Engineering (ICCAE)","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/A5111395978","display_name":"Kohei Kanada","orcid":null},"institutions":[{"id":"https://openalex.org/I96636082","display_name":"Meijo University","ror":"https://ror.org/04h42fc75","country_code":"JP","type":"education","lineage":["https://openalex.org/I96636082"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kohei Kanada","raw_affiliation_strings":["Graduate School of Science and Technology, Meijo University,Nagoya,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Meijo University,Nagoya,Japan","institution_ids":["https://openalex.org/I96636082"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064804883","display_name":"Shu Takemoto","orcid":"https://orcid.org/0009-0009-8861-2346"},"institutions":[{"id":"https://openalex.org/I96636082","display_name":"Meijo University","ror":"https://ror.org/04h42fc75","country_code":"JP","type":"education","lineage":["https://openalex.org/I96636082"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shu Takemoto","raw_affiliation_strings":["Meijo University,Faculty of Information Engineering,Nagoya,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meijo University,Faculty of Information Engineering,Nagoya,Japan","institution_ids":["https://openalex.org/I96636082"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078844713","display_name":"Yusuke Nozaki","orcid":"https://orcid.org/0000-0003-1369-8500"},"institutions":[{"id":"https://openalex.org/I96636082","display_name":"Meijo University","ror":"https://ror.org/04h42fc75","country_code":"JP","type":"education","lineage":["https://openalex.org/I96636082"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yusuke Nozaki","raw_affiliation_strings":["Meijo University,Faculty of Information Engineering,Nagoya,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meijo University,Faculty of Information Engineering,Nagoya,Japan","institution_ids":["https://openalex.org/I96636082"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102076246","display_name":"Masaya Yoshikawa","orcid":null},"institutions":[{"id":"https://openalex.org/I96636082","display_name":"Meijo University","ror":"https://ror.org/04h42fc75","country_code":"JP","type":"education","lineage":["https://openalex.org/I96636082"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaya Yoshikawa","raw_affiliation_strings":["Meijo University,Faculty of Information Engineering,Nagoya,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meijo University,Faculty of Information Engineering,Nagoya,Japan","institution_ids":["https://openalex.org/I96636082"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"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":0.04055064,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"192","last_page":"195"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9965999722480774,"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":0.9965999722480774,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9932000041007996,"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":0.9925000071525574,"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/computer-science","display_name":"Computer science","score":0.673747181892395},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.5792790651321411},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.5598043203353882},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.13493859767913818},{"id":"https://openalex.org/keywords/seismology","display_name":"Seismology","score":0.05777016282081604}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.673747181892395},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.5792790651321411},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.5598043203353882},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.13493859767913818},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.05777016282081604},{"id":"https://openalex.org/C77928131","wikidata":"https://www.wikidata.org/wiki/Q193343","display_name":"Tectonics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccae64891.2025.10980580","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccae64891.2025.10980580","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 17th International Conference on Computer and Automation Engineering (ICCAE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5037664951","display_name":null,"funder_award_id":"JP23K11112","funder_id":"https://openalex.org/F4320320212","funder_display_name":"Japan Society for the Promotion of Science London"}],"funders":[{"id":"https://openalex.org/F4320320212","display_name":"Japan Society for the Promotion of Science London","ror":"https://ror.org/02m7axw05"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1873763122","https://openalex.org/W2051267297","https://openalex.org/W2112796928","https://openalex.org/W2535690855","https://openalex.org/W4321471428","https://openalex.org/W4400611920","https://openalex.org/W6728757088"],"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/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Federated":[0,45],"learning":[1,25,57,78,93,131,143],"has":[2],"gained":[3],"increasing":[4],"attention":[5],"in":[6,9,75,129],"social":[7],"applications":[8],"recent":[10],"years.":[11],"However,":[12],"concerns":[13],"have":[14],"emerged":[15],"regarding":[16],"potential":[17,127],"threats":[18],"to":[19,52,91,108,121,140],"the":[20,44,61,76,96,102,119,126,147],"internal":[21],"information":[22],"security":[23,31,105],"of":[24,63,104,149],"models.":[26],"This":[27,49],"research":[28],"addresses":[29],"these":[30,110],"challenges":[32],"through":[33],"several":[34],"key":[35],"contributions:":[36],"We":[37,67],"propose":[38],"a":[39,54,81],"differential":[40,123],"privacy":[41,124],"implementation":[42],"for":[43],"Averaging":[46],"(FedAvg)":[47],"algorithm.":[48],"approach":[50],"aims":[51],"create":[53],"secure":[55],"federated":[56,77],"environment":[58],"while":[59,145],"preserving":[60,146],"benefits":[62],"FedAvg's":[64],"weighted":[65],"aggregation.":[66],"also":[68],"investigate":[69],"attack":[70],"scenarios":[71],"involving":[72],"malicious":[73],"participants":[74],"process,":[79],"with":[80],"particular":[82],"focus":[83],"on":[84],"model-reversal":[85,111],"attacks,":[86],"where":[87],"an":[88],"adversary":[89],"attempts":[90],"extract":[92],"data":[94],"from":[95],"global":[97],"model.":[98],"Finally,":[99],"we":[100,116],"evaluate":[101],"effectiveness":[103],"measures":[106],"designed":[107],"counter":[109],"attacks.":[112],"Through":[113],"extensive":[114],"experimentation,":[115],"analyze":[117],"both":[118],"ability":[120],"protect":[122],"and":[125],"vulnerabilities":[128],"collaborative":[130,142],"systems.":[132],"Our":[133],"findings":[134],"provide":[135],"valuable":[136],"insights":[137],"into":[138],"how":[139],"safeguard":[141],"systems":[144],"utility":[148],"real-world":[150],"applications.":[151]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}