{"id":"https://openalex.org/W4410057995","doi":"https://doi.org/10.32604/cmc.2025.062094","title":"A Two-Layer Network Intrusion Detection Method Incorporating LSTM and Stacking Ensemble Learning","display_name":"A Two-Layer Network Intrusion Detection Method Incorporating LSTM and Stacking Ensemble Learning","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4410057995","doi":"https://doi.org/10.32604/cmc.2025.062094"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.062094","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.062094","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.062094","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110195480","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0001-8932-6661"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jun Wang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081745945","display_name":"Changqiang Ge","orcid":"https://orcid.org/0009-0004-7536-0809"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chaoren Ge","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101937305","display_name":"Yihong Li","orcid":"https://orcid.org/0000-0002-0622-1969"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yihong Li","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075054710","display_name":"Huimin Zhao","orcid":"https://orcid.org/0000-0002-6877-2002"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huimin Zhao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109751759","display_name":"Qiang Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiang Fu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020994807","display_name":"Kerang Cao","orcid":"https://orcid.org/0000-0002-4053-7166"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kerang Cao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5033114960","display_name":"Hoe-Kyung Jung","orcid":"https://orcid.org/0000-0002-7607-1126"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hoekyung Jung","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5110195480"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.8751,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.97833832,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"83","issue":"3","first_page":"5129","last_page":"5153"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9390000104904175,"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":0.9390000104904175,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.8188983798027039},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.685827374458313},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6378092765808105},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.6121118068695068},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.6094201803207397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5724464058876038},{"id":"https://openalex.org/keywords/intrusion","display_name":"Intrusion","score":0.4817107319831848},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44782814383506775},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40930843353271484},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.23914194107055664},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.21243074536323547},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.1167498528957367},{"id":"https://openalex.org/keywords/geochemistry","display_name":"Geochemistry","score":0.08727943897247314},{"id":"https://openalex.org/keywords/nanotechnology","display_name":"Nanotechnology","score":0.0755372941493988}],"concepts":[{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.8188983798027039},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.685827374458313},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6378092765808105},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.6121118068695068},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.6094201803207397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5724464058876038},{"id":"https://openalex.org/C158251709","wikidata":"https://www.wikidata.org/wiki/Q354025","display_name":"Intrusion","level":2,"score":0.4817107319831848},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44782814383506775},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40930843353271484},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.23914194107055664},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.21243074536323547},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.1167498528957367},{"id":"https://openalex.org/C17409809","wikidata":"https://www.wikidata.org/wiki/Q161764","display_name":"Geochemistry","level":1,"score":0.08727943897247314},{"id":"https://openalex.org/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.0755372941493988},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.062094","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.062094","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.062094","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.062094","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2893123663","https://openalex.org/W3016669523","https://openalex.org/W3043530913","https://openalex.org/W3086638135","https://openalex.org/W3111066710","https://openalex.org/W3117495151","https://openalex.org/W3186153394","https://openalex.org/W3203436613","https://openalex.org/W4210743106","https://openalex.org/W4220846496","https://openalex.org/W4224058622","https://openalex.org/W4224126807","https://openalex.org/W4224220262","https://openalex.org/W4285678381","https://openalex.org/W4291226689","https://openalex.org/W4298110865","https://openalex.org/W4308422437","https://openalex.org/W4327750468","https://openalex.org/W4352976871","https://openalex.org/W4367312488","https://openalex.org/W4385522694","https://openalex.org/W4386645116","https://openalex.org/W4387335033","https://openalex.org/W4389477519","https://openalex.org/W4390755438","https://openalex.org/W4401560938","https://openalex.org/W4403117400","https://openalex.org/W4403243966"],"related_works":["https://openalex.org/W2035329725","https://openalex.org/W2070875936","https://openalex.org/W4250391473","https://openalex.org/W4302292679","https://openalex.org/W4241625287","https://openalex.org/W2050788868","https://openalex.org/W4295885776","https://openalex.org/W2027634686","https://openalex.org/W3036164038","https://openalex.org/W2133389611"],"abstract_inverted_index":{"Network":[0],"Intrusion":[1],"Detection":[2],"System":[3],"(NIDS)":[4],"detection":[5,26,36,122,147,177,204],"of":[6,28,109,124,146,189],"minority":[7,66,75,153],"class":[8,62,67,76,154],"attacks":[9,18,77],"is":[10],"always":[11],"a":[12,40,47,198],"difficult":[13],"task":[14],"when":[15],"dealing":[16],"with":[17,157],"in":[19,144,181,205],"complex":[20,192],"network":[21,56,89,96,135,193,207],"environments.":[22],"To":[23],"improve":[24],"the":[25,74,87,94,104,110,116,130,158,163,168,174,187],"capability":[27],"minority-class":[29,175,202],"attacks,":[30,63],"this":[31,182],"study":[32],"proposes":[33],"an":[34,51,120],"intrusion":[35],"method":[37],"based":[38],"on":[39,129],"two-layer":[41,164],"structure.":[42],"The":[43,69,82,179],"first":[44],"layer":[45,71],"employs":[46],"CNN-BiLSTM":[48],"model":[49,118],"incorporating":[50],"attention":[52],"mechanism":[53],"to":[54,102,191],"classify":[55],"traffic":[57],"into":[58],"normal":[59],"traffic,":[60],"majority":[61],"and":[64,93,106,127,133,149],"merged":[65],"attacks.":[68,155],"second":[70],"further":[72],"segments":[73],"through":[78],"Stacking":[79],"ensemble":[80],"learning.":[81],"datasets":[83],"are":[84],"selected":[85],"from":[86],"generic":[88],"dataset":[90,97,101],"CIC-IDS2017,":[91,131],"NSL-KDD,":[92,132],"industrial":[95,134,206],"Mississippi":[98],"Gas":[99],"Pipeline":[100],"enhance":[103],"generalization":[105],"practical":[107],"applicability":[108],"model.":[111],"Experimental":[112],"results":[113],"show":[114],"that":[115],"proposed":[117],"achieves":[119],"overall":[121],"accuracy":[123,148],"99%,":[125,126],"95%":[128],"datasets,":[136],"respectively.":[137],"It":[138],"also":[139,196],"significantly":[140],"outperforms":[141],"traditional":[142],"methods":[143],"terms":[145],"recall":[150],"rate":[151,171],"for":[152,201],"Compared":[156],"single-layer":[159],"deep":[160],"learning":[161],"model,":[162],"structure":[165],"effectively":[166],"reduces":[167],"false":[169],"alarm":[170],"while":[172],"improving":[173],"attack":[176,203],"performance.":[178],"research":[180],"paper":[183],"not":[184],"only":[185],"improves":[186],"adaptability":[188],"NIDS":[190],"environments":[194],"but":[195],"provides":[197],"new":[199],"solution":[200],"security.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}
