{"id":"https://openalex.org/W3174500793","doi":"https://doi.org/10.3390/s21134294","title":"Analysis of Autoencoders for Network Intrusion Detection","display_name":"Analysis of Autoencoders for Network Intrusion Detection","publication_year":2021,"publication_date":"2021-06-23","ids":{"openalex":"https://openalex.org/W3174500793","doi":"https://doi.org/10.3390/s21134294","mag":"3174500793","pmid":"https://pubmed.ncbi.nlm.nih.gov/34201798"},"language":"en","primary_location":{"id":"doi:10.3390/s21134294","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21134294","pdf_url":"https://www.mdpi.com/1424-8220/21/13/4294/pdf?version=1624602109","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/21/13/4294/pdf?version=1624602109","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072665849","display_name":"Youngrok Song","orcid":"https://orcid.org/0000-0001-6497-2659"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngrok Song","raw_affiliation_strings":["Department of AI, Sungkyunkwan University, Suwon 16419, Gyeonggi-do, Korea"],"affiliations":[{"raw_affiliation_string":"Department of AI, Sungkyunkwan University, Suwon 16419, Gyeonggi-do, Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102992568","display_name":"Sangwon Hyun","orcid":"https://orcid.org/0000-0003-2265-4518"},"institutions":[{"id":"https://openalex.org/I89440247","display_name":"Myongji University","ror":"https://ror.org/00s9dpb54","country_code":"KR","type":"education","lineage":["https://openalex.org/I89440247"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Sangwon Hyun","raw_affiliation_strings":["Department of Computer Engineering, Myongji University, Yongin 17058, Gyeonggi-do, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Myongji University, Yongin 17058, Gyeonggi-do, Korea","institution_ids":["https://openalex.org/I89440247"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087179276","display_name":"Yun-Gyung Cheong","orcid":"https://orcid.org/0000-0001-6329-8439"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Yun-Gyung Cheong","raw_affiliation_strings":["Department of AI, Sungkyunkwan University, Suwon 16419, Gyeonggi-do, Korea"],"affiliations":[{"raw_affiliation_string":"Department of AI, Sungkyunkwan University, Suwon 16419, Gyeonggi-do, Korea","institution_ids":["https://openalex.org/I848706"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5087179276","https://openalex.org/A5102992568"],"corresponding_institution_ids":["https://openalex.org/I848706","https://openalex.org/I89440247"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":17.4422,"has_fulltext":false,"cited_by_count":142,"citation_normalized_percentile":{"value":0.99514674,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"21","issue":"13","first_page":"4294","last_page":"4294"},"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9987000226974487,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9979000091552734,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9453465342521667},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8061790466308594},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.718264102935791},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6616880893707275},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.6599549651145935},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6505478620529175},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6309181451797485},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5555762648582458},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4825672209262848},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42880815267562866},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4169570803642273},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3629668056964874},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07456430792808533}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9453465342521667},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8061790466308594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.718264102935791},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6616880893707275},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.6599549651145935},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6505478620529175},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6309181451797485},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5555762648582458},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4825672209262848},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42880815267562866},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4169570803642273},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3629668056964874},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07456430792808533},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s21134294","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21134294","pdf_url":"https://www.mdpi.com/1424-8220/21/13/4294/pdf?version=1624602109","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:34201798","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34201798","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:87edb525bb34466bb138c650a67ca3ae","is_oa":true,"landing_page_url":"https://doaj.org/article/87edb525bb34466bb138c650a67ca3ae","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 21, Iss 13, p 4294 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/21/13/4294/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s21134294","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 21; Issue 13; Pages: 4294","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8272075","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8272075","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s21134294","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21134294","pdf_url":"https://www.mdpi.com/1424-8220/21/13/4294/pdf?version=1624602109","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.550000011920929,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3174500793.pdf","grobid_xml":"https://content.openalex.org/works/W3174500793.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W111228695","https://openalex.org/W1513904472","https://openalex.org/W1598201276","https://openalex.org/W1669806660","https://openalex.org/W1679074130","https://openalex.org/W2052387539","https://openalex.org/W2099940443","https://openalex.org/W2142889610","https://openalex.org/W2171949605","https://openalex.org/W2267339884","https://openalex.org/W2302958273","https://openalex.org/W2335999708","https://openalex.org/W2342408547","https://openalex.org/W2399941526","https://openalex.org/W2464796885","https://openalex.org/W2541841318","https://openalex.org/W2554148185","https://openalex.org/W2560162835","https://openalex.org/W2612398564","https://openalex.org/W2620760558","https://openalex.org/W2736937187","https://openalex.org/W2749908420","https://openalex.org/W2768211408","https://openalex.org/W2783741806","https://openalex.org/W2787957674","https://openalex.org/W2798248638","https://openalex.org/W2799758613","https://openalex.org/W2867534720","https://openalex.org/W2890474333","https://openalex.org/W2895182117","https://openalex.org/W2922628727","https://openalex.org/W2947802941","https://openalex.org/W2963197901","https://openalex.org/W2963262350","https://openalex.org/W2980576170","https://openalex.org/W2995305419","https://openalex.org/W2997091882","https://openalex.org/W3002328320","https://openalex.org/W3022604549","https://openalex.org/W3024012711","https://openalex.org/W3035311645","https://openalex.org/W3047526793","https://openalex.org/W3048960967","https://openalex.org/W3049204557","https://openalex.org/W3082841960","https://openalex.org/W3099937686","https://openalex.org/W3122864121","https://openalex.org/W3129437522","https://openalex.org/W3138102940","https://openalex.org/W3143021555","https://openalex.org/W6631190155","https://openalex.org/W6637397297","https://openalex.org/W6683718830","https://openalex.org/W6730018140"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W3088732000"],"abstract_inverted_index":{"As":[0],"network":[1],"attacks":[2,46],"are":[3,63],"constantly":[4],"and":[5,40,50,75,83,122,132],"dramatically":[6],"evolving,":[7],"demonstrating":[8],"new":[9],"patterns,":[10],"intelligent":[11],"Network":[12],"Intrusion":[13],"Detection":[14],"Systems":[15],"(NIDS),":[16],"using":[17,116,135],"deep-learning":[18],"techniques,":[19],"have":[20,31,152],"been":[21,32],"actively":[22],"studied":[23],"to":[24,38,77],"tackle":[25],"these":[26],"problems.":[27],"Recently,":[28],"various":[29],"autoencoders":[30,62,88,115],"used":[33],"for":[34],"NIDS":[35],"in":[36,65,91],"order":[37],"accurately":[39],"promptly":[41],"detect":[42],"unknown":[43,67],"types":[44,68],"of":[45,55,69,86,105,128,147],"(i.e.,":[47],"zero-day":[48],"attacks)":[49],"also":[51],"alleviate":[52],"the":[53,56,61,79,87,92,117,144,157],"burden":[54],"laborious":[57],"labeling":[58],"task.":[59],"Although":[60],"effective":[64],"detecting":[66],"attacks,":[70],"it":[71],"takes":[72],"tremendous":[73],"time":[74],"effort":[76],"find":[78],"optimal":[80],"model":[81,130,150],"architecture":[82],"hyperparameter":[84],"settings":[85],"that":[89,101,143],"result":[90],"best":[93],"detection":[94],"performance.":[95,159],"This":[96],"can":[97,151],"be":[98],"an":[99,148],"obstacle":[100],"hinders":[102],"practical":[103],"applications":[104],"autoencoder-based":[106],"NIDS.":[107],"To":[108],"address":[109],"this":[110],"challenge,":[111],"we":[112],"rigorously":[113],"study":[114],"benchmark":[118],"datasets,":[119],"NSL-KDD,":[120],"IoTID20,":[121],"N-BaIoT.":[123],"We":[124],"evaluate":[125],"multiple":[126],"combinations":[127],"different":[129],"structures":[131],"latent":[133,145],"sizes,":[134],"a":[136,153],"simple":[137],"autoencoder":[138,149],"model.":[139],"The":[140],"results":[141],"indicate":[142],"size":[146],"significant":[154],"impact":[155],"on":[156],"IDS":[158]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":40},{"year":2023,"cited_by_count":37},{"year":2022,"cited_by_count":31},{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-01T17:29:45.350535","created_date":"2025-10-10T00:00:00"}