{"id":"https://openalex.org/W4378676964","doi":"https://doi.org/10.1145/3590003.3590018","title":"An Intrusion Detection Model With Attention and BiLSTM-DNN","display_name":"An Intrusion Detection Model With Attention and BiLSTM-DNN","publication_year":2023,"publication_date":"2023-03-17","ids":{"openalex":"https://openalex.org/W4378676964","doi":"https://doi.org/10.1145/3590003.3590018"},"language":"en","primary_location":{"id":"doi:10.1145/3590003.3590018","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3590003.3590018","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 2nd Asia Conference on Algorithms, Computing and Machine Learning","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/A5001959760","display_name":"Yongcai Tao","orcid":"https://orcid.org/0000-0003-3098-3960"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongcai Tao","raw_affiliation_strings":["School of Computer and Artificial Intelligence, Zhengzhou University, China"],"raw_orcid":"https://orcid.org/0000-0003-3098-3960","affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, Zhengzhou University, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102015005","display_name":"Jitao Zhang","orcid":"https://orcid.org/0009-0004-0686-9484"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jitao Zhang","raw_affiliation_strings":["School of Cyber Science and Engineering, Zhengzhou University, China"],"raw_orcid":"https://orcid.org/0009-0004-0686-9484","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Zhengzhou University, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101530205","display_name":"Lin Wei","orcid":"https://orcid.org/0000-0002-5678-3417"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Wei","raw_affiliation_strings":["School of Cyber Science and Engineering, Zhengzhou University, China"],"raw_orcid":"https://orcid.org/0000-0002-5678-3417","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Zhengzhou University, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085521381","display_name":"Yufei Gao","orcid":"https://orcid.org/0000-0002-2356-0700"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yufei Gao","raw_affiliation_strings":["School of Cyber Science and Engineering, Zhengzhou University, China"],"raw_orcid":"https://orcid.org/0000-0002-2356-0700","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Zhengzhou University, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072249624","display_name":"Lei Shi","orcid":"https://orcid.org/0000-0002-1170-3911"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Shi","raw_affiliation_strings":["School of Cyber Science and Engineering, Zhengzhou University, China"],"raw_orcid":"https://orcid.org/0000-0002-1170-3911","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Zhengzhou University, China","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I38877650"],"apc_list":null,"apc_paid":null,"fwci":0.3755,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.59062235,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"78","last_page":"83"},"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":0.9983999729156494,"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":0.9980999827384949,"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":0.863335132598877},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7745366096496582},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7500964403152466},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.6792071461677551},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6763988733291626},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.590094268321991},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5687568783760071},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5240336060523987},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5235257148742676},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5144495964050293},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4599681496620178},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3994668424129486},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3605528175830841}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.863335132598877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7745366096496582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7500964403152466},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.6792071461677551},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6763988733291626},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.590094268321991},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5687568783760071},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5240336060523987},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5235257148742676},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5144495964050293},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4599681496620178},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3994668424129486},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3605528175830841}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3590003.3590018","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3590003.3590018","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 2nd Asia Conference on Algorithms, Computing and Machine Learning","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2394186609","https://openalex.org/W3042855339","https://openalex.org/W3131088496","https://openalex.org/W3143021555","https://openalex.org/W3171364527","https://openalex.org/W7103975904","https://openalex.org/W7104177099"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W2889302474","https://openalex.org/W3120400911","https://openalex.org/W4366990902","https://openalex.org/W4317732970","https://openalex.org/W4388550696","https://openalex.org/W4321636153","https://openalex.org/W2122022187","https://openalex.org/W4313289487","https://openalex.org/W2115529843"],"abstract_inverted_index":{"Abstract\u2014At":[0],"present,":[1],"machine":[2],"learning":[3,6],"and":[4,28,46,81,96,106,130,135],"deep":[5],"are":[7,109],"often":[8],"used":[9],"for":[10],"network":[11,33],"traffic":[12],"intrusion":[13,34,40],"detection.":[14],"In":[15],"order":[16],"to":[17,52,69,76],"solve":[18],"the":[19,30,61,92,112,121,124,133,141,144],"problem":[20],"of":[21,32,123,143],"unfocused":[22],"feature":[23,55],"extraction":[24,56],"in":[25],"these":[26],"methods":[27],"improve":[29],"accuracy":[31,122],"detection,":[35],"this":[36],"paper":[37],"proposes":[38],"an":[39],"detection":[41],"model":[42,49],"that":[43,120],"combines":[44],"Attention":[45,51],"BiLSTM-DNN(ABD).":[47],"The":[48,88,116],"uses":[50,67,74,91],"perform":[53],"preliminary":[54],"on":[57,132],"input":[58],"data,":[59],"reads":[60],"relationship":[62],"between":[63],"different":[64],"features,":[65,73,80],"then":[66],"BiLSTM":[68],"extract":[70,78],"long-distance":[71],"dependent":[72],"DNN":[75],"further":[77],"deep-level":[79],"finally":[82],"obtains":[83],"classification":[84],"through":[85],"SoftMax":[86],"classifier.":[87],"comparison":[89,113],"experiment":[90,114],"NSL_KDD":[93],"data":[94],"set,":[95],"models":[97],"such":[98],"as":[99,111],"BiLSTM-DNN,":[100],"support":[101],"vector":[102],"machine,":[103],"decision":[104],"tree":[105],"random":[107],"forest":[108],"selected":[110],"model.":[115],"experimental":[117],"results":[118],"show":[119],"ABD":[125],"is":[126],"improved":[127],"by":[128],"1.0%":[129],"2.0%":[131],"two-category":[134],"five-category":[136],"tasks,":[137],"respectively,":[138],"which":[139],"verifies":[140],"effectiveness":[142],"method.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
