{"id":"https://openalex.org/W4319264752","doi":"https://doi.org/10.1186/s40537-023-00694-8","title":"IGRF-RFE: a hybrid feature selection method for MLP-based network intrusion detection on UNSW-NB15 dataset","display_name":"IGRF-RFE: a hybrid feature selection method for MLP-based network intrusion detection on UNSW-NB15 dataset","publication_year":2023,"publication_date":"2023-02-05","ids":{"openalex":"https://openalex.org/W4319264752","doi":"https://doi.org/10.1186/s40537-023-00694-8"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-023-00694-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-023-00694-8","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00694-8","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00694-8","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033026799","display_name":"Yuhua Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I51158804","display_name":"Massey University","ror":"https://ror.org/052czxv31","country_code":"NZ","type":"education","lineage":["https://openalex.org/I51158804"]}],"countries":["NZ"],"is_corresponding":true,"raw_author_name":"Yuhua Yin","raw_affiliation_strings":["Comp Sci/Info Tech, Cybersecurity Lab, Massey University, Auckland, New Zealand"],"affiliations":[{"raw_affiliation_string":"Comp Sci/Info Tech, Cybersecurity Lab, Massey University, Auckland, New Zealand","institution_ids":["https://openalex.org/I51158804"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007979944","display_name":"Julian Jang\u2010Jaccard","orcid":"https://orcid.org/0000-0002-1002-057X"},"institutions":[{"id":"https://openalex.org/I51158804","display_name":"Massey University","ror":"https://ror.org/052czxv31","country_code":"NZ","type":"education","lineage":["https://openalex.org/I51158804"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Julian Jang-Jaccard","raw_affiliation_strings":["Comp Sci/Info Tech, Cybersecurity Lab, Massey University, Auckland, New Zealand"],"affiliations":[{"raw_affiliation_string":"Comp Sci/Info Tech, Cybersecurity Lab, Massey University, Auckland, New Zealand","institution_ids":["https://openalex.org/I51158804"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080488010","display_name":"Wen Xu","orcid":"https://orcid.org/0000-0003-0558-9558"},"institutions":[{"id":"https://openalex.org/I51158804","display_name":"Massey University","ror":"https://ror.org/052czxv31","country_code":"NZ","type":"education","lineage":["https://openalex.org/I51158804"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Wen Xu","raw_affiliation_strings":["Comp Sci/Info Tech, Cybersecurity Lab, Massey University, Auckland, New Zealand"],"affiliations":[{"raw_affiliation_string":"Comp Sci/Info Tech, Cybersecurity Lab, Massey University, Auckland, New Zealand","institution_ids":["https://openalex.org/I51158804"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075210141","display_name":"Amardeep Singh","orcid":"https://orcid.org/0000-0003-1916-3347"},"institutions":[{"id":"https://openalex.org/I51158804","display_name":"Massey University","ror":"https://ror.org/052czxv31","country_code":"NZ","type":"education","lineage":["https://openalex.org/I51158804"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Amardeep Singh","raw_affiliation_strings":["Comp Sci/Info Tech, Cybersecurity Lab, Massey University, Auckland, New Zealand"],"affiliations":[{"raw_affiliation_string":"Comp Sci/Info Tech, Cybersecurity Lab, Massey University, Auckland, New Zealand","institution_ids":["https://openalex.org/I51158804"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031626010","display_name":"Jinting Zhu","orcid":"https://orcid.org/0000-0002-0682-1796"},"institutions":[{"id":"https://openalex.org/I51158804","display_name":"Massey University","ror":"https://ror.org/052czxv31","country_code":"NZ","type":"education","lineage":["https://openalex.org/I51158804"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Jinting Zhu","raw_affiliation_strings":["Comp Sci/Info Tech, Cybersecurity Lab, Massey University, Auckland, New Zealand"],"affiliations":[{"raw_affiliation_string":"Comp Sci/Info Tech, Cybersecurity Lab, Massey University, Auckland, New Zealand","institution_ids":["https://openalex.org/I51158804"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087242242","display_name":"Fariza Sabrina","orcid":"https://orcid.org/0000-0002-8455-2499"},"institutions":[{"id":"https://openalex.org/I74899385","display_name":"Central Queensland University","ror":"https://ror.org/023q4bk22","country_code":"AU","type":"education","lineage":["https://openalex.org/I74899385"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Fariza Sabrina","raw_affiliation_strings":["School of Engineering and Technology, Central Queensland University, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Technology, Central Queensland University, Sydney, Australia","institution_ids":["https://openalex.org/I74899385"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078627842","display_name":"Jin Kwak","orcid":"https://orcid.org/0000-0001-6931-2705"},"institutions":[{"id":"https://openalex.org/I57664883","display_name":"Ajou University","ror":"https://ror.org/03tzb2h73","country_code":"KR","type":"education","lineage":["https://openalex.org/I57664883"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jin Kwak","raw_affiliation_strings":["Department of Cyber Security, Ajou University, Suwon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Cyber Security, Ajou University, Suwon, Republic of Korea","institution_ids":["https://openalex.org/I57664883"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5033026799"],"corresponding_institution_ids":["https://openalex.org/I51158804"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":55.4213,"has_fulltext":true,"cited_by_count":284,"citation_normalized_percentile":{"value":0.9998265,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"10","issue":"1","first_page":null,"last_page":null},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987000226974487,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.996999979019165,"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":0.7943251132965088},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7820808291435242},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6972019672393799},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.6361858248710632},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6020656824111938},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5984641313552856},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5554858446121216},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5398074984550476},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.4849698543548584},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4840623438358307},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.44954508543014526},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4364723861217499},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.41138726472854614},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40194225311279297},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3025035858154297},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.12672573328018188}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7943251132965088},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7820808291435242},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6972019672393799},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.6361858248710632},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6020656824111938},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5984641313552856},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5554858446121216},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5398074984550476},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.4849698543548584},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4840623438358307},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.44954508543014526},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4364723861217499},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.41138726472854614},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40194225311279297},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3025035858154297},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.12672573328018188},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-023-00694-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-023-00694-8","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00694-8","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1746c8593838417e8c0e867ecaf08e14","is_oa":true,"landing_page_url":"https://doaj.org/article/1746c8593838417e8c0e867ecaf08e14","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 10, Iss 1, Pp 1-26 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-023-00694-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-023-00694-8","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00694-8","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life in Land","score":0.6800000071525574,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4319264752.pdf"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W429766147","https://openalex.org/W1487321909","https://openalex.org/W1730693163","https://openalex.org/W1966741850","https://openalex.org/W1989540221","https://openalex.org/W2099940443","https://openalex.org/W2128064123","https://openalex.org/W2150847526","https://openalex.org/W2165313080","https://openalex.org/W2216946510","https://openalex.org/W2296509296","https://openalex.org/W2557913829","https://openalex.org/W2605307741","https://openalex.org/W2623293810","https://openalex.org/W2748773139","https://openalex.org/W2766585573","https://openalex.org/W2792290891","https://openalex.org/W2890645737","https://openalex.org/W2897765576","https://openalex.org/W2911278693","https://openalex.org/W2928048063","https://openalex.org/W2971986980","https://openalex.org/W2978631110","https://openalex.org/W2978801942","https://openalex.org/W2982676361","https://openalex.org/W3001675796","https://openalex.org/W3004777721","https://openalex.org/W3014732532","https://openalex.org/W3024333932","https://openalex.org/W3025093231","https://openalex.org/W3043530913","https://openalex.org/W3082814285","https://openalex.org/W3102376457","https://openalex.org/W3106741970","https://openalex.org/W3112106267","https://openalex.org/W3112742529","https://openalex.org/W3186962463","https://openalex.org/W3209469313","https://openalex.org/W3215200159","https://openalex.org/W3217115371","https://openalex.org/W4200327071","https://openalex.org/W4200608302","https://openalex.org/W4214714410","https://openalex.org/W4220658398","https://openalex.org/W4289236186","https://openalex.org/W6600755840"],"related_works":["https://openalex.org/W2076543106","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W2523437662","https://openalex.org/W4387048144","https://openalex.org/W2492135063","https://openalex.org/W2362514456","https://openalex.org/W2766585573","https://openalex.org/W4387490624","https://openalex.org/W4286643620"],"abstract_inverted_index":{"Abstract":[0],"The":[1,205],"effectiveness":[2],"of":[3,51,71,78,105,141,169,190,221],"machine":[4,147],"learning":[5],"models":[6],"can":[7,22,186,195],"be":[8,129],"significantly":[9],"averse":[10],"to":[11,90,128,158,215,227],"redundant":[12],"and":[13,59,85],"irrelevant":[14],"features":[15,108,127,199],"present":[16],"in":[17,124,131],"the":[18,49,68,92,103,111,132,138,167,178,188,202,209,218],"large":[19],"dataset":[20,180],"which":[21],"cause":[23],"drastic":[24],"performance":[25],"degradation.":[26],"This":[27],"paper":[28],"proposes":[29],"IGRF-RFE:":[30],"a":[31,42,53,60,76,146,153],"hybrid":[32],"feature":[33,93,133,155,161,203,210],"selection":[34],"method":[35,55,62,150,185],"tasked":[36],"for":[37,56,63],"multi-class":[38],"network":[39],"anomalies":[40],"using":[41],"multilayer":[43],"perceptron":[44],"(MLP)":[45],"network.":[46],"IGRF-RFE":[47],"exploits":[48],"qualities":[50],"both":[52],"filter":[54,80,101],"its":[57,64],"speed":[58],"wrapper":[61,149],"relevance":[65,168],"search.":[66],"In":[67,137],"first":[69],"phase":[70,140],"our":[72,142,183],"approach,":[73,143],"we":[74,144],"use":[75,145],"combination":[77],"two":[79,100],"methods,":[81,102],"information":[82],"gain":[83],"(IG)":[84],"random":[86],"forest":[87],"(RF)":[88],"respectively,":[89],"reduce":[91,160],"subset":[94,134],"search":[95,135],"space.":[96,136,204],"By":[97],"combining":[98],"these":[99],"influence":[104],"less":[106],"important":[107],"but":[109],"with":[110],"high-frequency":[112],"values":[113],"selected":[114],"by":[115,121],"IG":[116],"is":[117,211,223],"more":[118,125,197],"effectively":[119],"managed":[120],"RF":[122],"resulting":[123],"relevant":[126,198],"included":[130],"second":[139],"learning-based":[148],"that":[151,182,208],"provides":[152],"recursive":[154],"elimination":[156],"(RFE)":[157],"further":[159],"dimensions":[162],"while":[163,200,217],"taking":[164],"into":[165],"account":[166],"similar":[170],"features.":[171],"Our":[172],"experimental":[173],"results":[174,206],"obtained":[175],"based":[176],"on":[177],"UNSW-NB15":[179],"confirmed":[181],"proposed":[184],"improve":[187],"accuracy":[189,220],"anomaly":[191],"detection":[192],"as":[193],"it":[194],"select":[196],"reducing":[201],"show":[207],"reduced":[212],"from":[213,225],"42":[214],"23":[216],"multi-classification":[219],"MLP":[222],"improved":[224],"82.25%":[226],"84.24%.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":14},{"year":2025,"cited_by_count":99},{"year":2024,"cited_by_count":120},{"year":2023,"cited_by_count":45},{"year":2022,"cited_by_count":5},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}