{"id":"https://openalex.org/W3213628850","doi":"https://doi.org/10.1109/bcd51206.2021.9581420","title":"Intrusion Prediction using Long Short-Term Memory Deep Learning with UNSW-NB15","display_name":"Intrusion Prediction using Long Short-Term Memory Deep Learning with UNSW-NB15","publication_year":2021,"publication_date":"2021-09-13","ids":{"openalex":"https://openalex.org/W3213628850","doi":"https://doi.org/10.1109/bcd51206.2021.9581420","mag":"3213628850"},"language":"en","primary_location":{"id":"doi:10.1109/bcd51206.2021.9581420","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bcd51206.2021.9581420","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/ACIS 6th International Conference on Big Data, Cloud Computing, and Data Science (BCD)","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/A5113674501","display_name":"Seong-Soo Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I39815113","display_name":"Georgia Southern University","ror":"https://ror.org/04agmb972","country_code":"US","type":"education","lineage":["https://openalex.org/I39815113"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Seongsoo Kim","raw_affiliation_strings":["Department of Information Technology, Georgia Southern University, Statesboro, GA, U.S.A"],"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Georgia Southern University, Statesboro, GA, U.S.A","institution_ids":["https://openalex.org/I39815113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333466","display_name":"Lei Chen","orcid":"https://orcid.org/0000-0002-3919-8056"},"institutions":[{"id":"https://openalex.org/I39815113","display_name":"Georgia Southern University","ror":"https://ror.org/04agmb972","country_code":"US","type":"education","lineage":["https://openalex.org/I39815113"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["Department of Information Technology, Georgia Southern University, Statesboro, GA, U.S.A"],"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Georgia Southern University, Statesboro, GA, U.S.A","institution_ids":["https://openalex.org/I39815113"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047923732","display_name":"Jongyeop Kim","orcid":"https://orcid.org/0000-0002-1068-9855"},"institutions":[{"id":"https://openalex.org/I39815113","display_name":"Georgia Southern University","ror":"https://ror.org/04agmb972","country_code":"US","type":"education","lineage":["https://openalex.org/I39815113"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jongyeop Kim","raw_affiliation_strings":["Department of Information Technology, Georgia Southern University, Statesboro, GA, U.S.A"],"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Georgia Southern University, Statesboro, GA, U.S.A","institution_ids":["https://openalex.org/I39815113"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5113674501"],"corresponding_institution_ids":["https://openalex.org/I39815113"],"apc_list":null,"apc_paid":null,"fwci":0.4584,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.6656435,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"53","last_page":"59"},"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":0.996999979019165,"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":0.9944999814033508,"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":0.7227709293365479},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6388132572174072},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5896508097648621},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5310944318771362},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.4665633738040924},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4425407350063324},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.4373592734336853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38957399129867554},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2489437460899353},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.20366069674491882},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18901798129081726},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.112396240234375},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08186915516853333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7227709293365479},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6388132572174072},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5896508097648621},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5310944318771362},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.4665633738040924},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4425407350063324},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.4373592734336853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38957399129867554},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2489437460899353},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.20366069674491882},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18901798129081726},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.112396240234375},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08186915516853333},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bcd51206.2021.9581420","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bcd51206.2021.9581420","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/ACIS 6th International Conference on Big Data, Cloud Computing, and Data Science (BCD)","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":11,"referenced_works":["https://openalex.org/W1989129957","https://openalex.org/W2099940443","https://openalex.org/W2296509296","https://openalex.org/W2783291475","https://openalex.org/W2944643572","https://openalex.org/W2979925643","https://openalex.org/W3003685271","https://openalex.org/W3004752684","https://openalex.org/W3005630930","https://openalex.org/W3045966226","https://openalex.org/W3080469893"],"related_works":["https://openalex.org/W2353179089","https://openalex.org/W2923538289","https://openalex.org/W2353125546","https://openalex.org/W2470643824","https://openalex.org/W4400595174","https://openalex.org/W2349635380","https://openalex.org/W4353089801","https://openalex.org/W2353819554","https://openalex.org/W2359488321","https://openalex.org/W4401807425"],"abstract_inverted_index":{"This":[0],"study":[1],"shows":[2],"the":[3,14,76,84,90,96,105,108,113],"effectiveness":[4],"of":[5,41,92,107],"anomaly-based":[6],"IDS":[7],"using":[8,125],"long":[9],"short-term":[10],"memory(LSTM)":[11],"based":[12],"on":[13],"newly":[15],"developed":[16],"dataset":[17],"called":[18],"UNSW-NB15":[19],"while":[20,52],"considering":[21],"root":[22],"mean":[23,27],"square":[24],"error":[25,29],"and":[26,39,48,67,127],"absolute":[28],"as":[30,45],"evaluation":[31,128],"metrics":[32,131],"for":[33,72,119],"accuracy.":[34],"For":[35],"each":[36,73],"attack,":[37,95],"80%":[38],"90%":[40],"samples":[42],"were":[43],"used":[44],"LSTM":[46,126],"inputs":[47],"trained":[49],"this":[50,57,133],"model":[51,58],"increasing":[53],"epoch":[54],"values.":[55],"Furthermore,":[56],"has":[59],"predicted":[60],"attack":[61,70,74,86],"points":[62,71],"by":[63,112],"applying":[64],"test":[65],"data":[66,121],"produced":[68],"possible":[69],"at":[75],"3":[77],"<sup":[78],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[79],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">rd</sup>":[80],"time":[81],"frame":[82],"against":[83],"actual":[85],"point.":[87],"However,":[88],"in":[89,104],"case":[91],"an":[93],"Exploit":[94],"consecutive":[97],"overlapping":[98],"attacks":[99],"happen,":[100],"there":[101],"was":[102],"ambiguity":[103],"interpretation":[106],"numerical":[109],"values":[110,124],"calculated":[111],"LSTM.":[114],"We":[115],"presented":[116],"a":[117],"methodology":[118],"training":[120],"with":[122,129],"binary":[123],"RMSE":[130],"throughout":[132],"study.":[134]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}