{"id":"https://openalex.org/W4309375067","doi":"https://doi.org/10.1109/smc53654.2022.9945600","title":"Hybrid Network Intrusion Detection with Stacked Sparse Contractive Autoencoders and Attention-based Bidirectional LSTM","display_name":"Hybrid Network Intrusion Detection with Stacked Sparse Contractive Autoencoders and Attention-based Bidirectional LSTM","publication_year":2022,"publication_date":"2022-10-09","ids":{"openalex":"https://openalex.org/W4309375067","doi":"https://doi.org/10.1109/smc53654.2022.9945600"},"language":"en","primary_location":{"id":"doi:10.1109/smc53654.2022.9945600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc53654.2022.9945600","pdf_url":null,"source":{"id":"https://openalex.org/S4363607746","display_name":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5057935426","display_name":"Jing Bi","orcid":"https://orcid.org/0000-0002-4610-0141"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jing Bi","raw_affiliation_strings":["Beijing University of Technology,Faculty of Information Technology,Beijing,China,100124"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology,Faculty of Information Technology,Beijing,China,100124","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009051992","display_name":"Ziyue Guan","orcid":"https://orcid.org/0000-0001-8599-5155"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyue Guan","raw_affiliation_strings":["Beijing University of Technology,Faculty of Information Technology,Beijing,China,100124"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology,Faculty of Information Technology,Beijing,China,100124","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101881295","display_name":"Haitao Yuan","orcid":"https://orcid.org/0000-0001-8475-419X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haitao Yuan","raw_affiliation_strings":["Beihang University,School of Automation Science and Electrical Engineering,Beijing,China,100191"],"affiliations":[{"raw_affiliation_string":"Beihang University,School of Automation Science and Electrical Engineering,Beijing,China,100191","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5057935426"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.216,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.3413515,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"6","last_page":"11"},"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":0.9991999864578247,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9962000250816345,"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":0.8284825086593628},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7007346153259277},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.6688388586044312},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5741958618164062},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5419872403144836},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4935663938522339},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.43783101439476013},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42915672063827515},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.36423876881599426},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.357612669467926},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.2763820290565491}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8284825086593628},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7007346153259277},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.6688388586044312},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5741958618164062},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5419872403144836},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4935663938522339},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.43783101439476013},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42915672063827515},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36423876881599426},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.357612669467926},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.2763820290565491},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc53654.2022.9945600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc53654.2022.9945600","pdf_url":null,"source":{"id":"https://openalex.org/S4363607746","display_name":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1561369259","https://openalex.org/W2752217602","https://openalex.org/W2788805965","https://openalex.org/W2793747891","https://openalex.org/W2884397828","https://openalex.org/W2894660140","https://openalex.org/W2914227855","https://openalex.org/W3022634314","https://openalex.org/W3034863102","https://openalex.org/W3087100893","https://openalex.org/W3106165797","https://openalex.org/W3109073683","https://openalex.org/W3113154577","https://openalex.org/W3130425349","https://openalex.org/W3156959920","https://openalex.org/W3162584529","https://openalex.org/W3163315201","https://openalex.org/W4200597037"],"related_works":["https://openalex.org/W2357468538","https://openalex.org/W1577110157","https://openalex.org/W2355007334","https://openalex.org/W2390009783","https://openalex.org/W4254602698","https://openalex.org/W2394461323","https://openalex.org/W2349441905","https://openalex.org/W2361044160","https://openalex.org/W1483130311","https://openalex.org/W2388497169"],"abstract_inverted_index":{"Accurately":[0],"identifying":[1],"network":[2,13,38,52],"intrusion":[3,39,53],"cannot":[4],"only":[5],"help":[6],"individuals":[7],"and":[8,64,68,124],"enterprises":[9],"better":[10],"deal":[11],"with":[12,25,81],"security":[14],"problems,":[15],"but":[16],"also":[17],"maintain":[18],"the":[19,37,73,82,103,108,111,126,138],"Internet":[20],"environment.":[21],"Currently,":[22],"classification":[23,47,83,119,148],"methods":[24],"autoencoders":[26,80,93],"for":[27,36,51,96,107],"feature":[28,74],"learning":[29],"have":[30],"been":[31],"proved":[32],"to":[33,102,117],"be":[34],"suitable":[35],"detection.":[40,54],"This":[41],"work":[42],"proposes":[43],"a":[44],"new":[45],"hybrid":[46],"method":[48],"named":[49],"SABD":[50,55,71,140],"integrates":[56,72],"Stacked":[57],"sparse":[58,78,91],"contractive":[59,79,92],"autoencoders,":[60],"Attention-based":[61],"Bidirectional":[62],"long-term":[63],"short-term":[65],"memory":[66],"(LSTM),":[67],"Decision":[69],"fusion.":[70],"extraction":[75],"of":[76,85,121,147],"stacked":[77,90],"ability":[84],"attention-based":[86,104],"bidirectional":[87,105],"LSTM.":[88],"Specifically,":[89],"are":[94,100],"used":[95],"extracting":[97],"features,":[98],"which":[99],"sent":[101],"LSTM":[106],"classification.":[109],"Finally,":[110],"decision":[112],"fusion":[113],"algorithm":[114],"is":[115],"adopted":[116],"integrate":[118],"results":[120,130],"multiple":[122],"classifiers":[123],"yield":[125],"final":[127],"results.":[128],"Experimental":[129],"based":[131],"on":[132],"real-life":[133],"UNSW-NB15":[134],"data":[135],"demonstrate":[136],"that":[137],"proposed":[139],"outperforms":[141],"its":[142],"state-of-the-art":[143],"peers":[144],"in":[145],"terms":[146],"accuracy.":[149]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}