{"id":"https://openalex.org/W4415934105","doi":"https://doi.org/10.1109/nof66640.2025.11223310","title":"FedPEAC-Net: Federated Intrusion Detection via Autoencoder-Based Feature Selection and Hybrid Neural Modeling","display_name":"FedPEAC-Net: Federated Intrusion Detection via Autoencoder-Based Feature Selection and Hybrid Neural Modeling","publication_year":2025,"publication_date":"2025-09-30","ids":{"openalex":"https://openalex.org/W4415934105","doi":"https://doi.org/10.1109/nof66640.2025.11223310"},"language":null,"primary_location":{"id":"doi:10.1109/nof66640.2025.11223310","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nof66640.2025.11223310","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 16th International Conference on Network of the Future (NoF)","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":null,"display_name":"Ricardo A. Lundgren","orcid":null},"institutions":[{"id":"https://openalex.org/I3121799822","display_name":"Universidade Federal do Piau\u00ed","ror":"https://ror.org/00kwnx126","country_code":"BR","type":"education","lineage":["https://openalex.org/I3121799822"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Ricardo A. Lundgren","raw_affiliation_strings":["Universidade Federal Flumimense &#x2013; UFF,LabGen/M&#x00ED;diaCom &#x2013; PPGEET/TET/PGC/TCC,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade Federal Flumimense &#x2013; UFF,LabGen/M&#x00ED;diaCom &#x2013; PPGEET/TET/PGC/TCC,Brazil","institution_ids":["https://openalex.org/I3121799822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025711863","display_name":"Tadeu N. Ferreira","orcid":"https://orcid.org/0000-0002-9964-9699"},"institutions":[{"id":"https://openalex.org/I161127581","display_name":"Universidade Federal Fluminense","ror":"https://ror.org/02rjhbb08","country_code":"BR","type":"education","lineage":["https://openalex.org/I161127581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Tadeu N. Ferreira","raw_affiliation_strings":["Universidade Federal Flumimense &#x2013; UFF,LaProp &#x2013; PPGEET/TET,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade Federal Flumimense &#x2013; UFF,LaProp &#x2013; PPGEET/TET,Brazil","institution_ids":["https://openalex.org/I161127581"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076412136","display_name":"Diogo M. F. Mattos","orcid":"https://orcid.org/0000-0002-1279-7366"},"institutions":[{"id":"https://openalex.org/I3121799822","display_name":"Universidade Federal do Piau\u00ed","ror":"https://ror.org/00kwnx126","country_code":"BR","type":"education","lineage":["https://openalex.org/I3121799822"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Diogo M. F. Mattos","raw_affiliation_strings":["Universidade Federal Flumimense &#x2013; UFF,LabGen/M&#x00ED;diaCom &#x2013; PPGEET/TET/PGC/TCC,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade Federal Flumimense &#x2013; UFF,LabGen/M&#x00ED;diaCom &#x2013; PPGEET/TET/PGC/TCC,Brazil","institution_ids":["https://openalex.org/I3121799822"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":0.33733423,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"72","last_page":"80"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9402999877929688,"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"}},"topics":[{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9402999877929688,"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"}},{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.0071000000461936,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.00419999985024333,"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/intrusion-detection-system","display_name":"Intrusion detection system","score":0.7145000100135803},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6783999800682068},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.652400016784668},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5443000197410583},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48820000886917114},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.421099990606308},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3993000090122223},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.3962000012397766},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3668999969959259}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7878999710083008},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.7145000100135803},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6783999800682068},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.652400016784668},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6287999749183655},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5443000197410583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5302000045776367},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48820000886917114},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4740000069141388},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.421099990606308},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3993000090122223},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.3962000012397766},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3668999969959259},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3562999963760376},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.3458000123500824},{"id":"https://openalex.org/C137524506","wikidata":"https://www.wikidata.org/wiki/Q2247688","display_name":"Anomaly-based intrusion detection system","level":3,"score":0.3156999945640564},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.29010000824928284},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C2780707294","wikidata":"https://www.wikidata.org/wiki/Q27795853","display_name":"Effi","level":2,"score":0.2849999964237213},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.27630001306533813},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.2703999876976013},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.259799987077713},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C158251709","wikidata":"https://www.wikidata.org/wiki/Q354025","display_name":"Intrusion","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/nof66640.2025.11223310","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nof66640.2025.11223310","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 16th International Conference on Network of the Future (NoF)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2735582123","https://openalex.org/W2789828921","https://openalex.org/W2889136050","https://openalex.org/W2909444216","https://openalex.org/W3106741970","https://openalex.org/W3121972055","https://openalex.org/W3157871125","https://openalex.org/W3189042227","https://openalex.org/W3198303278","https://openalex.org/W3212137514","https://openalex.org/W4213328526","https://openalex.org/W4221146354","https://openalex.org/W4285620290","https://openalex.org/W4361010174","https://openalex.org/W4366966548","https://openalex.org/W4393210605","https://openalex.org/W4393931133"],"related_works":[],"abstract_inverted_index":{"The":[0,81,97],"accelerated":[1],"growth":[2],"of":[3,13,24,29,37,105,125,167],"the":[4,11,17,22,27,33,87,133,139,163,168],"Internet":[5],"and":[6,35,64,108,120,127,155,165],"smart":[7],"devices":[8],"has":[9],"increased":[10],"volume":[12],"data":[14],"generated":[15],"at":[16],"network":[18],"edge,":[19],"also":[20,131],"raising":[21],"incidence":[23],"attacks":[25],"targeting":[26],"exploitation":[28],"sensitive":[30],"information.":[31],"Thus,":[32],"relevance":[34],"necessity":[36],"distributed,":[38],"efficient":[39],"Intrusion":[40],"Detection":[41],"Systems":[42],"(IDS)":[43],"that":[44,60,100],"preserve":[45],"user":[46],"privacy":[47],"become":[48],"evident.":[49],"This":[50],"paper":[51],"proposes":[52],"FedPEAC-Net,":[53],"an":[54,62,103],"IDS":[55],"based":[56],"on":[57],"federated":[58,92,147],"learning":[59],"combines":[61],"autoencoder":[63],"a":[65,73,91,115],"binary":[66],"classifier":[67],"trained":[68],"in":[69,90,171],"parallel,":[70],"integrated":[71],"with":[72,86,94,175],"feature":[74,111],"selection":[75],"technique":[76],"guided":[77],"by":[78],"reconstruction":[79],"error.":[80],"adopted":[82],"methodology":[83],"involves":[84],"experimentation":[85],"CICIDS2017":[88],"dataset":[89],"scenario":[93],"10":[95],"clients.":[96],"results":[98,161],"show":[99],"FedPEAC-Net":[101,130],"achieves":[102],"F1-score":[104],"0.95":[106],"before":[107],"0.93":[109],"after":[110],"selection,":[112],"showing":[113],"only":[114],"2.3%":[116],"drop,":[117],"while":[118],"ResNet":[119],"LeNet-5":[121,154],"models":[122],"showed":[123],"reductions":[124],"15.6%":[126],"15%,":[128],"respectively.":[129],"achieved":[132],"lowest":[134],"total":[135],"training":[136],"time":[137],"among":[138],"evaluated":[140],"models,":[141],"attaining":[142],"542":[143],"seconds":[144,152,157],"over":[145],"20":[146],"rounds,":[148],"compared":[149],"to":[150],"819":[151],"for":[153,158],"1742":[156],"ResNet.":[159],"These":[160],"confirm":[162],"effectiveness":[164],"efficiency":[166],"proposed":[169],"approach":[170],"distributed":[172],"environments,":[173],"even":[174],"resource-constrained":[176],"devices.":[177]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-05T00:00:00"}
