{"id":"https://openalex.org/W4214643830","doi":"https://doi.org/10.2478/jaiscr-2022-0010","title":"An Autoencoder-Enhanced Stacking Neural Network Model for Increasing the Performance of Intrusion Detection","display_name":"An Autoencoder-Enhanced Stacking Neural Network Model for Increasing the Performance of Intrusion Detection","publication_year":2021,"publication_date":"2021-04-01","ids":{"openalex":"https://openalex.org/W4214643830","doi":"https://doi.org/10.2478/jaiscr-2022-0010"},"language":"en","primary_location":{"id":"doi:10.2478/jaiscr-2022-0010","is_oa":true,"landing_page_url":"https://doi.org/10.2478/jaiscr-2022-0010","pdf_url":"https://www.sciendo.com/pdf/10.2478/jaiscr-2022-0010","source":{"id":"https://openalex.org/S4210223945","display_name":"Journal of Artificial Intelligence and Soft Computing Research","issn_l":"2083-2567","issn":["2083-2567","2449-6499"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317241","host_organization_name":"Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology","host_organization_lineage":["https://openalex.org/P4310317241"],"host_organization_lineage_names":["Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Artificial Intelligence and Soft Computing Research","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.sciendo.com/pdf/10.2478/jaiscr-2022-0010","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020723171","display_name":"Csaba Brunner","orcid":null},"institutions":[{"id":"https://openalex.org/I163245316","display_name":"Corvinus University of Budapest","ror":"https://ror.org/01vxfm326","country_code":"HU","type":"education","lineage":["https://openalex.org/I163245316"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Csaba Brunner","raw_affiliation_strings":["Department of Information Systems , Corvinus University of Budapest F\u0151v\u00e1m t\u00e9r 13-15 , Budapest , Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems , Corvinus University of Budapest F\u0151v\u00e1m t\u00e9r 13-15 , Budapest , Hungary","institution_ids":["https://openalex.org/I163245316"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012791570","display_name":"Andrea K\u0151","orcid":"https://orcid.org/0000-0003-0023-1143"},"institutions":[{"id":"https://openalex.org/I163245316","display_name":"Corvinus University of Budapest","ror":"https://ror.org/01vxfm326","country_code":"HU","type":"education","lineage":["https://openalex.org/I163245316"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Andrea K\u0151","raw_affiliation_strings":["Department of Information Systems , Corvinus University of Budapest F\u0151v\u00e1m t\u00e9r 13-15 , Budapest , Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems , Corvinus University of Budapest F\u0151v\u00e1m t\u00e9r 13-15 , Budapest , Hungary","institution_ids":["https://openalex.org/I163245316"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033021961","display_name":"Szabina Fodor","orcid":"https://orcid.org/0000-0001-5459-7912"},"institutions":[{"id":"https://openalex.org/I163245316","display_name":"Corvinus University of Budapest","ror":"https://ror.org/01vxfm326","country_code":"HU","type":"education","lineage":["https://openalex.org/I163245316"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Szabina Fodor","raw_affiliation_strings":["Department of Computer Science , Corvinus University of Budapest F\u0151v\u00e1m t\u00e9r 13-15 , Budapest , Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , Corvinus University of Budapest F\u0151v\u00e1m t\u00e9r 13-15 , Budapest , Hungary","institution_ids":["https://openalex.org/I163245316"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0464,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.91750795,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"12","issue":"2","first_page":"149","last_page":"163"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":1.0,"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":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9983999729156494,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9955999851226807,"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":0.8281956911087036},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.7839717864990234},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6490615606307983},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.640748918056488},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.605399489402771},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5761623978614807},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5557180047035217},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5477612614631653},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5405437350273132}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8281956911087036},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.7839717864990234},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6490615606307983},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.640748918056488},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.605399489402771},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5761623978614807},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5557180047035217},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5477612614631653},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5405437350273132},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.2478/jaiscr-2022-0010","is_oa":true,"landing_page_url":"https://doi.org/10.2478/jaiscr-2022-0010","pdf_url":"https://www.sciendo.com/pdf/10.2478/jaiscr-2022-0010","source":{"id":"https://openalex.org/S4210223945","display_name":"Journal of Artificial Intelligence and Soft Computing Research","issn_l":"2083-2567","issn":["2083-2567","2449-6499"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317241","host_organization_name":"Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology","host_organization_lineage":["https://openalex.org/P4310317241"],"host_organization_lineage_names":["Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Artificial Intelligence and Soft Computing Research","raw_type":"journal-article"},{"id":"pmh:oai:unipub.lib.uni-corvinus.hu:7276","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400280","display_name":"Corvinus Research Archive (Corvinus University of Budapest)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I163245316","host_organization_name":"Corvinus University of Budapest","host_organization_lineage":["https://openalex.org/I163245316"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":{"id":"doi:10.2478/jaiscr-2022-0010","is_oa":true,"landing_page_url":"https://doi.org/10.2478/jaiscr-2022-0010","pdf_url":"https://www.sciendo.com/pdf/10.2478/jaiscr-2022-0010","source":{"id":"https://openalex.org/S4210223945","display_name":"Journal of Artificial Intelligence and Soft Computing Research","issn_l":"2083-2567","issn":["2083-2567","2449-6499"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317241","host_organization_name":"Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology","host_organization_lineage":["https://openalex.org/P4310317241"],"host_organization_lineage_names":["Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Artificial Intelligence and Soft Computing Research","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4214643830.pdf","grobid_xml":"https://content.openalex.org/works/W4214643830.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W141002133","https://openalex.org/W1437335841","https://openalex.org/W1530215515","https://openalex.org/W1541939527","https://openalex.org/W1840208138","https://openalex.org/W1963911016","https://openalex.org/W1966809779","https://openalex.org/W1981399499","https://openalex.org/W1994847875","https://openalex.org/W2068878071","https://openalex.org/W2076143961","https://openalex.org/W2099940443","https://openalex.org/W2101109743","https://openalex.org/W2106411961","https://openalex.org/W2108501770","https://openalex.org/W2113207845","https://openalex.org/W2160598920","https://openalex.org/W2167287136","https://openalex.org/W2168508521","https://openalex.org/W2189149359","https://openalex.org/W2192203593","https://openalex.org/W2271840356","https://openalex.org/W2296509296","https://openalex.org/W2342408547","https://openalex.org/W2399941526","https://openalex.org/W2527999453","https://openalex.org/W2552899443","https://openalex.org/W2678934292","https://openalex.org/W2742334953","https://openalex.org/W2749908420","https://openalex.org/W2762776925","https://openalex.org/W2789828921","https://openalex.org/W2790583291","https://openalex.org/W2807998075","https://openalex.org/W2890235427","https://openalex.org/W2890474333","https://openalex.org/W2901312569","https://openalex.org/W2904969546","https://openalex.org/W2944555271","https://openalex.org/W2947802941","https://openalex.org/W2963518686","https://openalex.org/W3001683812","https://openalex.org/W3040394052","https://openalex.org/W3045925899","https://openalex.org/W3047793363","https://openalex.org/W3048377462","https://openalex.org/W3126752450","https://openalex.org/W3135708040"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4386815338","https://openalex.org/W2145836866","https://openalex.org/W2803255133"],"abstract_inverted_index":{"Abstract":[0],"Security":[1],"threats,":[2],"among":[3],"other":[4],"intrusions":[5],"affecting":[6],"the":[7,38,49,94,127,143,150],"availability,":[8],"confidentiality":[9],"and":[10,15,20,92,104,133],"integrity":[11],"of":[12,40,71,96,100,123,129,145],"IT":[13],"resources":[14],"services,":[16],"are":[17],"spreading":[18],"fast":[19],"can":[21,47,62,172],"cause":[22],"serious":[23],"harm":[24],"to":[25,75,141,160],"organizations.":[26],"Intrusion":[27],"detection":[28,51,80],"has":[29],"a":[30,77,110,153],"key":[31],"role":[32],"in":[33,44,65,157,176],"capturing":[34],"intrusions.":[35],"In":[36,87],"particular,":[37],"application":[39,128],"machine":[41,84],"learning":[42,85],"methods":[43],"this":[45,88],"area":[46],"enrich":[48],"intrusion":[50,66,79,118,158],"efficiency.":[52],"Various":[53],"methods,":[54],"such":[55],"as":[56],"pattern":[57],"recognition":[58],"from":[59],"event":[60],"logs,":[61],"be":[63],"applied":[64],"detection.":[67,119],"The":[68,120,164],"main":[69,121],"goal":[70],"our":[72,124,146,162,169],"research":[73],"is":[74,126],"present":[76],"possible":[78],"approach":[81,116],"using":[82],"recent":[83],"techniques.":[86],"paper,":[89],"we":[90],"suggest":[91],"evaluate":[93],"usage":[95],"stacked":[97,134],"ensembles":[98,135],"consisting":[99],"neural":[101],"network":[102],"(SNN)":[103],"autoen-coder":[105],"(AE)":[106],"models":[107,171],"augmented":[108],"with":[109,174],"tree-structured":[111],"Parzen":[112],"estimator":[113],"hyperparameter":[114,131],"optimization":[115,132],"for":[117],"contribution":[122],"work":[125],"advanced":[130],"together.":[136],"We":[137,148],"conducted":[138],"several":[139],"experiments":[140],"check":[142],"effectiveness":[144],"approach.":[147],"used":[149],"NSL-KDD":[151],"dataset,":[152],"common":[154],"benchmark":[155],"dataset":[156],"detection,":[159],"train":[161],"models.":[163,181],"comparative":[165],"results":[166],"demonstrate":[167],"that":[168],"proposed":[170],"compete":[173],"and,":[175],"some":[177],"cases,":[178],"outperform":[179],"existing":[180]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}