{"id":"https://openalex.org/W4410486681","doi":"https://doi.org/10.1186/s42400-024-00295-9","title":"Privacy preserving federated learning with convolutional variational bottlenecks","display_name":"Privacy preserving federated learning with convolutional variational bottlenecks","publication_year":2025,"publication_date":"2025-05-20","ids":{"openalex":"https://openalex.org/W4410486681","doi":"https://doi.org/10.1186/s42400-024-00295-9"},"language":"en","primary_location":{"id":"doi:10.1186/s42400-024-00295-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42400-024-00295-9","pdf_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-024-00295-9","source":{"id":"https://openalex.org/S3035238565","display_name":"Cybersecurity","issn_l":"2523-3246","issn":["2523-3246"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybersecurity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-024-00295-9","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085699453","display_name":"Daniel Scheliga","orcid":"https://orcid.org/0000-0002-6469-7068"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Daniel Scheliga","raw_affiliation_strings":["Department of Computer Science and Automation, Technische Universit\u00e4t Ilmenau, Helmholtzplatz 5, 98693, Ilmenau, Thuringia, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Automation, Technische Universit\u00e4t Ilmenau, Helmholtzplatz 5, 98693, Ilmenau, Thuringia, Germany","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063243817","display_name":"Patrick M\u00e4der","orcid":"https://orcid.org/0000-0001-6871-2707"},"institutions":[{"id":"https://openalex.org/I76198965","display_name":"Friedrich Schiller University Jena","ror":"https://ror.org/05qpz1x62","country_code":"DE","type":"education","lineage":["https://openalex.org/I76198965"]},{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Patrick M\u00e4der","raw_affiliation_strings":["Department of Computer Science and Automation, Technische Universit\u00e4t Ilmenau, Helmholtzplatz 5, 98693, Ilmenau, Thuringia, Germany","Faculty of Biological Sciences, Friedrich Schiller University, Jena, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Automation, Technische Universit\u00e4t Ilmenau, Helmholtzplatz 5, 98693, Ilmenau, Thuringia, Germany","institution_ids":["https://openalex.org/I119449181"]},{"raw_affiliation_string":"Faculty of Biological Sciences, Friedrich Schiller University, Jena, Germany","institution_ids":["https://openalex.org/I76198965"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030228799","display_name":"Marco Seeland","orcid":"https://orcid.org/0000-0001-7204-3972"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marco Seeland","raw_affiliation_strings":["Department of Computer Science and Automation, Technische Universit\u00e4t Ilmenau, Helmholtzplatz 5, 98693, Ilmenau, Thuringia, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Automation, Technische Universit\u00e4t Ilmenau, Helmholtzplatz 5, 98693, Ilmenau, Thuringia, Germany","institution_ids":["https://openalex.org/I119449181"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5085699453"],"corresponding_institution_ids":["https://openalex.org/I119449181"],"apc_list":null,"apc_paid":null,"fwci":10.6317,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.97832704,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"8","issue":"1","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":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":0.9973999857902527,"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":0.9962999820709229,"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":0.7467750310897827},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.5438539981842041},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.47075751423835754},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3701493740081787},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.271945059299469}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7467750310897827},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5438539981842041},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.47075751423835754},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3701493740081787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.271945059299469}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s42400-024-00295-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42400-024-00295-9","pdf_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-024-00295-9","source":{"id":"https://openalex.org/S3035238565","display_name":"Cybersecurity","issn_l":"2523-3246","issn":["2523-3246"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybersecurity","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6ad1f524dadb4445a53b32155c7161ab","is_oa":true,"landing_page_url":"https://doaj.org/article/6ad1f524dadb4445a53b32155c7161ab","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Cybersecurity, Vol 8, Iss 1, Pp 1-22 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s42400-024-00295-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42400-024-00295-9","pdf_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-024-00295-9","source":{"id":"https://openalex.org/S3035238565","display_name":"Cybersecurity","issn_l":"2523-3246","issn":["2523-3246"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybersecurity","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5497106275","display_name":null,"funder_award_id":"5575/10-3","funder_id":"https://openalex.org/F4320326724","funder_display_name":"Th\u00fcringer Ministerium f\u00fcr Wirtschaft, Wissenschaft und Digitale Gesellschaft"}],"funders":[{"id":"https://openalex.org/F4320326724","display_name":"Th\u00fcringer Ministerium f\u00fcr Wirtschaft, Wissenschaft und Digitale Gesellschaft","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410486681.pdf","grobid_xml":"https://content.openalex.org/works/W4410486681.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1726806267","https://openalex.org/W2051434435","https://openalex.org/W2103559027","https://openalex.org/W2112796928","https://openalex.org/W2133665775","https://openalex.org/W2184652140","https://openalex.org/W2774510177","https://openalex.org/W2989289980","https://openalex.org/W2995022099","https://openalex.org/W3012561096","https://openalex.org/W3042621011","https://openalex.org/W3091870957","https://openalex.org/W3110068734","https://openalex.org/W3125616445","https://openalex.org/W3136620885","https://openalex.org/W3138815606","https://openalex.org/W3213330817","https://openalex.org/W4213044365","https://openalex.org/W4241535675","https://openalex.org/W4242422263","https://openalex.org/W4242657867","https://openalex.org/W4285555619","https://openalex.org/W4288345394","https://openalex.org/W4295806247","https://openalex.org/W4313396675","https://openalex.org/W4317436377","https://openalex.org/W4375798903","https://openalex.org/W4385187849","https://openalex.org/W4391661654","https://openalex.org/W4402354447","https://openalex.org/W6600157417","https://openalex.org/W6600339963","https://openalex.org/W6600350647","https://openalex.org/W6601048975","https://openalex.org/W6603827241","https://openalex.org/W6604801084","https://openalex.org/W6607110455"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4298221930","https://openalex.org/W2390279801","https://openalex.org/W2777914285","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W3176937389","https://openalex.org/W4408069290"],"abstract_inverted_index":{"Abstract":[0],"Gradient":[1],"Inversion":[2],"(GI)":[3],"attacks":[4,76,112],"are":[5,228],"a":[6,38,100,181,186,199],"ubiquitous":[7],"threat":[8],"in":[9,99,154,198],"Federated":[10],"Learning":[11],"as":[12,180],"they":[13],"exploit":[14],"gradient":[15,29],"leakage":[16,30],"to":[17,27,77,167,230,242,261],"reconstruct":[18],"supposedly":[19],"private":[20],"training":[21],"data.":[22],"Recent":[23],"work":[24],"has":[25],"proposed":[26,239],"prevent":[28,109],"without":[31,202],"loss":[32],"of":[33,72,93,106,126,142,160,175],"model":[34,169,177,216],"utility":[35,170],"by":[36,128,237],"incorporating":[37],"PRivacy":[39],"EnhanCing":[40],"mODulE":[41],"(PRECODE)":[42],"based":[43],"on":[44,74,213],"variational":[45,86,148],"modeling.":[46],"Without":[47],"further":[48],"analysis,":[49],"it":[50],"was":[51],"shown":[52],"that":[53,85,120,147,225,246],"PRECODE":[54,73,94,127,161],"successfully":[55],"protects":[56],"against":[57],"GI":[58,75,111,231],"attacks.":[59],"In":[60],"this":[61],"paper,":[62],"we":[63,68,116,184,244],"make":[64],"multiple":[65],"contributions.":[66],"First,":[67],"investigate":[69],"the":[70,91,96,122,138,155,172],"effect":[71,125,141],"reveal":[78],"its":[79],"underlying":[80],"working":[81],"principle.":[82],"We":[83,207,223],"show":[84,245],"modeling":[87,149],"introduces":[88],"stochasticity":[89],"into":[90],"gradients":[92,105,132],"and":[95,171,218,255,258],"subsequent":[97],"layers":[98,108],"neural":[101,200],"network.":[102,156],"The":[103],"stochastic":[104,131],"these":[107,205],"iterative":[110],"from":[113,204],"converging.":[114],"Second,":[115],"formulate":[117],"an":[118,209],"attack":[119,134],"disables":[121],"privacy":[123,139,188,249],"preserving":[124,140],"purposefully":[129],"omitting":[130],"during":[133],"optimization.":[135],"To":[136],"preserve":[137,263],"PRECODE,":[143,243],"our":[144,238,247],"analysis":[145],"reveals":[146],"must":[150],"be":[151,195,235],"placed":[152,196],"early":[153,158,197],"However,":[157],"placement":[159],"is":[162],"typically":[163],"not":[164],"feasible":[165],"due":[166],"reduced":[168],"exploding":[173],"number":[174],"additional":[176],"parameters.":[178],"Therefore,":[179],"third":[182],"contribution,":[183],"propose":[185],"novel":[187,248],"module\u2014the":[189],"Convolutional":[190],"Variational":[191],"Bottleneck":[192],"(CVB)\u2014that":[193],"can":[194,234],"network":[201],"suffering":[203],"drawbacks.":[206],"conduct":[208],"extensive":[210],"empirical":[211],"study":[212],"three":[214],"seminal":[215],"architectures":[217,227],"six":[219],"image":[220],"classification":[221],"datasets.":[222],"find":[224],"all":[226],"susceptible":[229],"attacks,":[232],"which":[233],"prevented":[236],"CVB.":[240],"Compared":[241],"module":[250],"requires":[251],"fewer":[252],"trainable":[253],"parameters,":[254],"thus":[256],"computational":[257],"communication":[259],"costs,":[260],"effectively":[262],"privacy.":[264]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}
