{"id":"https://openalex.org/W4246277246","doi":"https://doi.org/10.1145/3495018.3495042","title":"A New Intrusion Detection Method for the Industrial Internet","display_name":"A New Intrusion Detection Method for the Industrial Internet","publication_year":2021,"publication_date":"2021-10-23","ids":{"openalex":"https://openalex.org/W4246277246","doi":"https://doi.org/10.1145/3495018.3495042"},"language":"en","primary_location":{"id":"doi:10.1145/3495018.3495042","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3495018.3495042","pdf_url":null,"source":{"id":"https://openalex.org/S4363607741","display_name":"2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture","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":"https://openalex.org/A5014310702","display_name":"Yuhong Wu","orcid":"https://orcid.org/0000-0003-0692-440X"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhong Wu","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101427963","display_name":"Xiangdong Hu","orcid":"https://orcid.org/0000-0001-5496-6685"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangdong Hu","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036933525","display_name":"Minxia Huo","orcid":null},"institutions":[{"id":"https://openalex.org/I4210118050","display_name":"Taishan University","ror":"https://ror.org/02bpnkx55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210118050"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minxia Huo","raw_affiliation_strings":["Taishan College of Science and Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Taishan College of Science and Technology, China","institution_ids":["https://openalex.org/I4210118050"]}]}],"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":0.2700495,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"138","last_page":"146"},"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/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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9973000288009644,"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/softmax-function","display_name":"Softmax function","score":0.8866070508956909},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7937251329421997},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.7645293474197388},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.7384821772575378},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6400592923164368},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.6109508872032166},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5277976393699646},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4851582646369934},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.44249227643013},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4308820068836212},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4256010353565216},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4184831380844116},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39247554540634155},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3276098966598511},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.19000175595283508}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.8866070508956909},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7937251329421997},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.7645293474197388},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.7384821772575378},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6400592923164368},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.6109508872032166},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5277976393699646},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4851582646369934},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.44249227643013},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4308820068836212},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4256010353565216},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4184831380844116},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39247554540634155},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3276098966598511},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.19000175595283508},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3495018.3495042","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3495018.3495042","pdf_url":null,"source":{"id":"https://openalex.org/S4363607741","display_name":"2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W146900863","https://openalex.org/W641576740","https://openalex.org/W2762776925","https://openalex.org/W2803280656","https://openalex.org/W2960015156","https://openalex.org/W3025126107"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W3108503355","https://openalex.org/W4226420367","https://openalex.org/W2962876041","https://openalex.org/W3090555870","https://openalex.org/W3022820045","https://openalex.org/W2118717649","https://openalex.org/W2801655600","https://openalex.org/W3120400911"],"abstract_inverted_index":{"Current":[0],"network":[1,50,56,72],"data":[2],"are":[3,15],"massive,":[4],"high-dimensional,":[5],"temporal,":[6],"and":[7,9,35,51,74,86,122],"nonlinear,":[8],"attacks":[10],"against":[11],"the":[12,60,64,69,91,101,111,115,124],"industrial":[13],"Internet":[14],"changing":[16],"rapidly.":[17],"The":[18],"existing":[19],"intrusion":[20,42],"detection":[21,33,43],"methods":[22],"have":[23],"some":[24],"shortcomings,":[25],"such":[26],"as":[27],"difficulty":[28],"in":[29,59],"feature":[30],"extraction,":[31],"low":[32],"rate,":[34],"poor":[36],"generalizability.":[37],"Therefore,":[38],"a":[39,47],"deep":[40,48,70],"hybrid":[41],"model":[44],"that":[45],"integrates":[46],"belief":[49,71],"bidirectional":[52,75],"long":[53,76],"short-term":[54,77],"memory":[55,78],"was":[57,66,94],"proposed":[58,112],"present":[61],"work.":[62],"First,":[63],"dataset":[65,103],"preprocessed;":[67],"second,":[68],"(DBN)":[73],"(BiLSTM)":[79],"were":[80],"used":[81,95],"to":[82,96],"extract":[83],"nonlinear":[84],"features":[85],"long-distance":[87],"dependent":[88],"information.":[89],"Finally,":[90],"Softmax":[92],"classifier":[93],"identify":[97],"intrusions.":[98],"Experiments":[99],"on":[100],"UNSW-NB15":[102],"showed":[104],"that,":[105],"compared":[106],"with":[107],"current":[108],"leading":[109],"methods,":[110],"method":[113],"improved":[114],"accuracy":[116],"by":[117,128],"an":[118,129],"average":[119,130],"of":[120,131],"2.40%,":[121],"reduced":[123],"false":[125],"positive":[126],"rate":[127],"4.17%.":[132]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
