{"id":"https://openalex.org/W7130596212","doi":"https://doi.org/10.1109/ictc66702.2025.11388644","title":"Lightweight Hybrid Network Intrusion Detection Method based on AutoEncoder-XGBoost","display_name":"Lightweight Hybrid Network Intrusion Detection Method based on AutoEncoder-XGBoost","publication_year":2025,"publication_date":"2025-10-14","ids":{"openalex":"https://openalex.org/W7130596212","doi":"https://doi.org/10.1109/ictc66702.2025.11388644"},"language":null,"primary_location":{"id":"doi:10.1109/ictc66702.2025.11388644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc66702.2025.11388644","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 Information and Communication Technology Convergence (ICTC)","raw_type":"proceedings-article"},"type":"conference-paper","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":"Won Seok Choi","orcid":null},"institutions":[{"id":"https://openalex.org/I163753206","display_name":"Chungbuk National University","ror":"https://ror.org/02wnxgj78","country_code":"KR","type":"education","lineage":["https://openalex.org/I163753206"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Won Seok Choi","raw_affiliation_strings":["Chungbuk National University,Research Institude for Computer and Information Communication,Chungju,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chungbuk National University,Research Institude for Computer and Information Communication,Chungju,Republic of Korea","institution_ids":["https://openalex.org/I163753206"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126414298","display_name":"Bum Su Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I119575151","display_name":"Korea National University of Transportation","ror":"https://ror.org/03qqbe534","country_code":"KR","type":"education","lineage":["https://openalex.org/I119575151"]},{"id":"https://openalex.org/I163753206","display_name":"Chungbuk National University","ror":"https://ror.org/02wnxgj78","country_code":"KR","type":"education","lineage":["https://openalex.org/I163753206"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Bum Su Kim","raw_affiliation_strings":["Chungbuk National University,School of Information and Communication Engineering,Chungju,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chungbuk National University,School of Information and Communication Engineering,Chungju,Republic of Korea","institution_ids":["https://openalex.org/I119575151","https://openalex.org/I163753206"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090298544","display_name":"Hyeon Ho Lee","orcid":"https://orcid.org/0000-0002-0375-8410"},"institutions":[{"id":"https://openalex.org/I119575151","display_name":"Korea National University of Transportation","ror":"https://ror.org/03qqbe534","country_code":"KR","type":"education","lineage":["https://openalex.org/I119575151"]},{"id":"https://openalex.org/I163753206","display_name":"Chungbuk National University","ror":"https://ror.org/02wnxgj78","country_code":"KR","type":"education","lineage":["https://openalex.org/I163753206"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyeon Ho Lee","raw_affiliation_strings":["Chungbuk National University,School of Information and Communication Engineering,Chungju,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chungbuk National University,School of Information and Communication Engineering,Chungju,Republic of Korea","institution_ids":["https://openalex.org/I119575151","https://openalex.org/I163753206"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026721662","display_name":"Seong Gon Choi","orcid":"https://orcid.org/0000-0002-5326-8321"},"institutions":[{"id":"https://openalex.org/I119575151","display_name":"Korea National University of Transportation","ror":"https://ror.org/03qqbe534","country_code":"KR","type":"education","lineage":["https://openalex.org/I119575151"]},{"id":"https://openalex.org/I163753206","display_name":"Chungbuk National University","ror":"https://ror.org/02wnxgj78","country_code":"KR","type":"education","lineage":["https://openalex.org/I163753206"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seong Gon Choi","raw_affiliation_strings":["Chungbuk National University,School of Information and Communication Engineering,Chungju,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chungbuk National University,School of Information and Communication Engineering,Chungju,Republic of Korea","institution_ids":["https://openalex.org/I119575151","https://openalex.org/I163753206"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"849","last_page":"852"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9060999751091003,"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":0.9060999751091003,"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/T10714","display_name":"Software-Defined Networks and 5G","score":0.023600000888109207,"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":0.009499999694526196,"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/autoencoder","display_name":"Autoencoder","score":0.880299985408783},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.7495999932289124},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.47859999537467957},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47699999809265137},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.40149998664855957},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.36809998750686646},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.31540000438690186},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3089999854564667}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.880299985408783},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.7495999932289124},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7351999878883362},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5268999934196472},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.47859999537467957},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47699999809265137},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.424699991941452},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4171999990940094},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4146000146865845},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.40149998664855957},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36809998750686646},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.31540000438690186},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C137524506","wikidata":"https://www.wikidata.org/wiki/Q2247688","display_name":"Anomaly-based intrusion detection system","level":3,"score":0.3059999942779541},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.25380000472068787},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ictc66702.2025.11388644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc66702.2025.11388644","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 Information and Communication Technology Convergence (ICTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W4206933520","https://openalex.org/W4223531348","https://openalex.org/W4226077550","https://openalex.org/W4393145967","https://openalex.org/W4403484816"],"related_works":[],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,37,42],"lightweight":[3,38],"hybrid":[4],"network":[5],"intrusion":[6,49],"detection":[7,50,90,110],"method":[8],"based":[9],"on":[10,29],"AutoEncoder":[11,44],"and":[12,24,45,55,62,104,112],"XGBoost":[13],"for":[14,60,71,84],"use":[15],"in":[16,116],"resource-constrained":[17],"environments":[18],"such":[19,85],"as":[20],"small-scale":[21],"networks,":[22],"smartphones,":[23],"personal":[25],"computers.":[26],"Without":[27],"relying":[28],"complex":[30],"additional":[31],"modules,":[32],"the":[33,52,68,94,97,102],"proposed":[34,98],"system":[35,103],"employs":[36],"pipeline":[39],"consisting":[40],"of":[41,96],"single":[43],"XGBoost,":[46],"enabling":[47],"high-performance":[48],"without":[51],"high":[53,109],"memory":[54],"computational":[56],"demands":[57],"typically":[58],"required":[59],"training":[61],"inference.":[63],"In":[64],"addition,":[65],"to":[66],"improve":[67],"learning":[69],"rate":[70],"sparse":[72],"attack":[73],"traffic":[74],"types,":[75],"we":[76,100],"apply":[77],"Generative":[78],"Adversarial":[79],"Network":[80],"(GAN)-based":[81],"data":[82],"augmentation":[83],"traffic,":[86],"thereby":[87],"enhancing":[88],"overall":[89],"performance.":[91],"To":[92],"evaluate":[93],"effectiveness":[95],"method,":[99],"implemented":[101],"confirmed":[105],"that":[106],"it":[107],"achieves":[108],"rates":[111],"practical":[113],"applicability":[114],"even":[115],"resource-limited":[117],"environments.":[118]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-02-20T00:00:00"}