{"id":"https://openalex.org/W3008764542","doi":"https://doi.org/10.1109/isspit47144.2019.9001867","title":"Development of an Efficient Network Intrusion Detection Model Using Extreme Gradient Boosting (XGBoost) on the UNSW-NB15 Dataset","display_name":"Development of an Efficient Network Intrusion Detection Model Using Extreme Gradient Boosting (XGBoost) on the UNSW-NB15 Dataset","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3008764542","doi":"https://doi.org/10.1109/isspit47144.2019.9001867","mag":"3008764542"},"language":"en","primary_location":{"id":"doi:10.1109/isspit47144.2019.9001867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isspit47144.2019.9001867","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","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/A5031059767","display_name":"Anwar Husain","orcid":"https://orcid.org/0000-0002-0639-4093"},"institutions":[{"id":"https://openalex.org/I87552059","display_name":"Hood College","ror":"https://ror.org/04e6ngf61","country_code":"US","type":"education","lineage":["https://openalex.org/I87552059"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Anwar Husain","raw_affiliation_strings":["Department of Computer Science & Information Technology, Hood College, Frederick, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Information Technology, Hood College, Frederick, MD, USA","institution_ids":["https://openalex.org/I87552059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103045221","display_name":"Ahmed Salem","orcid":"https://orcid.org/0000-0002-0456-2276"},"institutions":[{"id":"https://openalex.org/I87552059","display_name":"Hood College","ror":"https://ror.org/04e6ngf61","country_code":"US","type":"education","lineage":["https://openalex.org/I87552059"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ahmed Salem","raw_affiliation_strings":["Department of Computer Science & Information Technology, Hood College, Frederick, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Information Technology, Hood College, Frederick, MD, USA","institution_ids":["https://openalex.org/I87552059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007104884","display_name":"Carol Jim","orcid":null},"institutions":[{"id":"https://openalex.org/I87552059","display_name":"Hood College","ror":"https://ror.org/04e6ngf61","country_code":"US","type":"education","lineage":["https://openalex.org/I87552059"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carol Jim","raw_affiliation_strings":["Department of Computer Science & Information Technology, Hood College, Frederick, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Information Technology, Hood College, Frederick, MD, USA","institution_ids":["https://openalex.org/I87552059"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080245391","display_name":"G. Dimitoglou","orcid":"https://orcid.org/0000-0003-2672-3787"},"institutions":[{"id":"https://openalex.org/I87552059","display_name":"Hood College","ror":"https://ror.org/04e6ngf61","country_code":"US","type":"education","lineage":["https://openalex.org/I87552059"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George Dimitoglou","raw_affiliation_strings":["Department of Computer Science & Information Technology, Hood College, Frederick, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Information Technology, Hood College, Frederick, MD, USA","institution_ids":["https://openalex.org/I87552059"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5031059767"],"corresponding_institution_ids":["https://openalex.org/I87552059"],"apc_list":null,"apc_paid":null,"fwci":3.0063,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.92295607,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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":0.9897000193595886,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9894000291824341,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.794755756855011},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.6005704402923584},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5398061275482178},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5034767985343933},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.45737791061401367},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.44999751448631287},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4340517520904541},{"id":"https://openalex.org/keywords/usable","display_name":"USable","score":0.42317166924476624},{"id":"https://openalex.org/keywords/network-security","display_name":"Network security","score":0.4198816418647766},{"id":"https://openalex.org/keywords/attack-model","display_name":"Attack model","score":0.4196837246417999},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34538745880126953},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1927521526813507},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.13975173234939575},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.1040453314781189}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.794755756855011},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.6005704402923584},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5398061275482178},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5034767985343933},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.45737791061401367},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.44999751448631287},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4340517520904541},{"id":"https://openalex.org/C2780615836","wikidata":"https://www.wikidata.org/wiki/Q2471869","display_name":"USable","level":2,"score":0.42317166924476624},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.4198816418647766},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.4196837246417999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34538745880126953},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1927521526813507},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.13975173234939575},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.1040453314781189},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isspit47144.2019.9001867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isspit47144.2019.9001867","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6499999761581421}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1526458608","https://openalex.org/W1586994930","https://openalex.org/W1591480890","https://openalex.org/W1988918299","https://openalex.org/W2031163547","https://openalex.org/W2099384706","https://openalex.org/W2099940443","https://openalex.org/W2101109743","https://openalex.org/W2103414007","https://openalex.org/W2117646649","https://openalex.org/W2279785795","https://openalex.org/W2295598076","https://openalex.org/W2296509296","https://openalex.org/W2334853001","https://openalex.org/W2342408547","https://openalex.org/W2570296101","https://openalex.org/W2600328926","https://openalex.org/W2734728597","https://openalex.org/W2743483681","https://openalex.org/W2752087956","https://openalex.org/W2755475540","https://openalex.org/W2797915143","https://openalex.org/W3102476541","https://openalex.org/W4236468428","https://openalex.org/W4247555314","https://openalex.org/W4399647672","https://openalex.org/W6635263116","https://openalex.org/W6743822681","https://openalex.org/W6869608176"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W4310224730","https://openalex.org/W2766514146","https://openalex.org/W4289703016","https://openalex.org/W2885516856","https://openalex.org/W3094138326"],"abstract_inverted_index":{"Network":[0],"intrusion":[1,15,46,169],"detection":[2],"systems":[3],"are":[4,17,175],"used":[5,164],"to":[6,19,38,40,48,55,78,109,126,148,177],"help":[7,127],"protect":[8],"and":[9,21,25,36,43,74,98,179],"secure":[10],"network":[11,14,27,45,50,72,75,129,168,182],"infrastructures.":[12],"Efficient":[13],"models":[16],"required":[18],"analyze":[20,42],"assess":[22],"both":[23],"present":[24],"future":[26,167],"attacks.":[28],"Various":[29],"machine":[30,87],"learning":[31,88],"methods":[32],"have":[33],"been":[34],"developed":[35,158],"evaluated":[37,64],"attempt":[39],"efficiently":[41,180],"predict":[44,181],"attacks":[47,73],"determine":[49],"attributes":[51],"that":[52,94,156],"may":[53,162],"contribute":[54],"a":[56,111,143],"particular":[57,144],"attack":[58,130,150,183],"type.":[59,151],"In":[60],"this":[61],"study,":[62],"we":[63,135],"the":[65,79,138],"UNSW-NB15":[66],"data":[67,83,100,170],"set,":[68],"represents":[69],"modern":[70],"day":[71],"traffic":[76],"compared":[77],"previous":[80],"standard":[81],"KDD99":[82],"set.":[84],"Among":[85],"various":[86],"algorithms,":[89],"extreme":[90],"gradient":[91],"boosting":[92],"(XGBoost)":[93],"provides":[95],"highly":[96],"efficient":[97],"accurate":[99],"predictive":[101],"model":[102,155],"were":[103,107],"used.":[104],"We":[105],"also":[106],"able":[108],"select":[110],"subset":[112],"of":[113,116,140],"23":[114,160,173],"out":[115],"39":[117],"usable":[118],"features":[119,174],"using":[120],"information":[121],"gain":[122],"obtained":[123],"through":[124],"XGBoost":[125,154],"distinguish":[128],"types.":[131,184],"Through":[132],"bivariate":[133],"analysis,":[134],"could":[136],"compute":[137],"percentage":[139],"records":[141],"in":[142],"value":[145],"range":[146],"correspond":[147],"an":[149],"The":[152],"final":[153],"was":[157],"uses":[159],"features,":[161],"be":[163],"for":[165],"any":[166],"where":[171],"these":[172],"available":[176],"easily":[178]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
