{"id":"https://openalex.org/W4388729307","doi":"https://doi.org/10.3390/jcp3040037","title":"A Hybrid Dimensionality Reduction for Network Intrusion Detection","display_name":"A Hybrid Dimensionality Reduction for Network Intrusion Detection","publication_year":2023,"publication_date":"2023-11-16","ids":{"openalex":"https://openalex.org/W4388729307","doi":"https://doi.org/10.3390/jcp3040037"},"language":"en","primary_location":{"id":"doi:10.3390/jcp3040037","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jcp3040037","pdf_url":"https://www.mdpi.com/2624-800X/3/4/37/pdf?version=1700123726","source":{"id":"https://openalex.org/S4210232532","display_name":"Journal of Cybersecurity and Privacy","issn_l":"2624-800X","issn":["2624-800X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"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 Cybersecurity and Privacy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2624-800X/3/4/37/pdf?version=1700123726","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111019612","display_name":"Humera Ghani","orcid":null},"institutions":[{"id":"https://openalex.org/I126193024","display_name":"London Metropolitan University","ror":"https://ror.org/00ae33288","country_code":"GB","type":"education","lineage":["https://openalex.org/I126193024"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Humera Ghani","raw_affiliation_strings":["School of Computing and Digital Media, London Metropolitan University, London N7 8DB, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Digital Media, London Metropolitan University, London N7 8DB, UK","institution_ids":["https://openalex.org/I126193024"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000146099","display_name":"Shahram Salekzamankhani","orcid":null},"institutions":[{"id":"https://openalex.org/I126193024","display_name":"London Metropolitan University","ror":"https://ror.org/00ae33288","country_code":"GB","type":"education","lineage":["https://openalex.org/I126193024"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shahram Salekzamankhani","raw_affiliation_strings":["School of Computing and Digital Media, London Metropolitan University, London N7 8DB, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Digital Media, London Metropolitan University, London N7 8DB, UK","institution_ids":["https://openalex.org/I126193024"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079514173","display_name":"Bal S. Virdee","orcid":"https://orcid.org/0000-0001-7203-0039"},"institutions":[{"id":"https://openalex.org/I126193024","display_name":"London Metropolitan University","ror":"https://ror.org/00ae33288","country_code":"GB","type":"education","lineage":["https://openalex.org/I126193024"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Bal Virdee","raw_affiliation_strings":["School of Computing and Digital Media, London Metropolitan University, London N7 8DB, UK"],"raw_orcid":"https://orcid.org/0000-0001-7203-0039","affiliations":[{"raw_affiliation_string":"School of Computing and Digital Media, London Metropolitan University, London N7 8DB, UK","institution_ids":["https://openalex.org/I126193024"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5111019612"],"corresponding_institution_ids":["https://openalex.org/I126193024"],"apc_list":{"value":1000,"currency":"CHF","value_usd":1207},"apc_paid":{"value":1000,"currency":"CHF","value_usd":1207},"fwci":1.7222,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.8458927,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"3","issue":"4","first_page":"830","last_page":"843"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9998000264167786,"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":0.9998000264167786,"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/T12326","display_name":"Network Packet Processing and Optimization","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.989300012588501,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7024798393249512},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6875935196876526},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6697440147399902},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6651731133460999},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6143035888671875},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5839973092079163},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5548819899559021},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.5456124544143677},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5331282615661621},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5319350957870483},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.5310300588607788},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.520440399646759},{"id":"https://openalex.org/keywords/weighted-voting","display_name":"Weighted voting","score":0.5055646896362305},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5048556923866272},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4548620879650116},{"id":"https://openalex.org/keywords/false-positive-rate","display_name":"False positive rate","score":0.4546036124229431},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33163976669311523},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.2639574110507965}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7024798393249512},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6875935196876526},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6697440147399902},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6651731133460999},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6143035888671875},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5839973092079163},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5548819899559021},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.5456124544143677},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5331282615661621},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5319350957870483},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.5310300588607788},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.520440399646759},{"id":"https://openalex.org/C132778050","wikidata":"https://www.wikidata.org/wiki/Q2065430","display_name":"Weighted voting","level":4,"score":0.5055646896362305},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5048556923866272},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4548620879650116},{"id":"https://openalex.org/C95922358","wikidata":"https://www.wikidata.org/wiki/Q5432725","display_name":"False positive rate","level":2,"score":0.4546036124229431},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33163976669311523},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.2639574110507965},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/jcp3040037","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jcp3040037","pdf_url":"https://www.mdpi.com/2624-800X/3/4/37/pdf?version=1700123726","source":{"id":"https://openalex.org/S4210232532","display_name":"Journal of Cybersecurity and Privacy","issn_l":"2624-800X","issn":["2624-800X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"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 Cybersecurity and Privacy","raw_type":"journal-article"},{"id":"pmh:oai:repository.londonmet.ac.uk:8888","is_oa":true,"landing_page_url":"https://repository.londonmet.ac.uk/8888/1/published%20accepted%2010-11-2023%20jcp-03-00037.pdf","pdf_url":"https://repository.londonmet.ac.uk/8888/1/published%20accepted%2010-11-2023%20jcp-03-00037.pdf","source":{"id":"https://openalex.org/S4306400140","display_name":"London Met Repository (London Metropolitan University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126193024","host_organization_name":"London Metropolitan University","host_organization_lineage":["https://openalex.org/I126193024"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:44349a3df4e24326b0ea0f1bd82fa1a5","is_oa":true,"landing_page_url":"https://doaj.org/article/44349a3df4e24326b0ea0f1bd82fa1a5","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Cybersecurity and Privacy, Vol 3, Iss 4, Pp 830-843 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/jcp3040037","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jcp3040037","pdf_url":"https://www.mdpi.com/2624-800X/3/4/37/pdf?version=1700123726","source":{"id":"https://openalex.org/S4210232532","display_name":"Journal of Cybersecurity and Privacy","issn_l":"2624-800X","issn":["2624-800X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"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 Cybersecurity and Privacy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388729307.pdf","grobid_xml":"https://content.openalex.org/works/W4388729307.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W2087016914","https://openalex.org/W2143426320","https://openalex.org/W2278186031","https://openalex.org/W2296509296","https://openalex.org/W2334853001","https://openalex.org/W2517563311","https://openalex.org/W2570296101","https://openalex.org/W2579582149","https://openalex.org/W2810550035","https://openalex.org/W2886020981","https://openalex.org/W2901492899","https://openalex.org/W2909444216","https://openalex.org/W2920086614","https://openalex.org/W2982676361","https://openalex.org/W2992625249","https://openalex.org/W3004752684","https://openalex.org/W3004777721","https://openalex.org/W3024333932","https://openalex.org/W3082729101","https://openalex.org/W3086419524","https://openalex.org/W3106741970","https://openalex.org/W3130980823","https://openalex.org/W3138465682","https://openalex.org/W3156346068","https://openalex.org/W3165183550","https://openalex.org/W3168793901","https://openalex.org/W3189826552","https://openalex.org/W3212457727","https://openalex.org/W4211114749","https://openalex.org/W4223531348","https://openalex.org/W4224231191","https://openalex.org/W4236137412","https://openalex.org/W4285093070","https://openalex.org/W4308119167","https://openalex.org/W4319264752","https://openalex.org/W4328125166","https://openalex.org/W6782983528","https://openalex.org/W6790819751","https://openalex.org/W6809774241"],"related_works":["https://openalex.org/W4322721277","https://openalex.org/W4312560343","https://openalex.org/W2096510549","https://openalex.org/W3182625625","https://openalex.org/W2913388591","https://openalex.org/W1750746579","https://openalex.org/W2026770740","https://openalex.org/W2130574884","https://openalex.org/W4388450686","https://openalex.org/W2142995730"],"abstract_inverted_index":{"Due":[0],"to":[1,41,204],"the":[2,43,48,52,75,87,145,149,154,159,173,197,205],"wide":[3],"variety":[4],"of":[5,11,27,98,115,153],"network":[6],"services,":[7],"many":[8],"different":[9],"types":[10],"protocols":[12],"exist,":[13],"producing":[14],"various":[15],"packet":[16],"features.":[17],"Some":[18],"features":[19,29,88,101,168],"contain":[20],"irrelevant":[21],"and":[22,33,46,67,124,142,166,192],"redundant":[23],"information.":[24],"The":[25,105,130],"presence":[26],"such":[28],"increases":[30],"computational":[31],"complexity":[32],"decreases":[34],"accuracy.":[35],"Therefore,":[36],"this":[37],"research":[38],"is":[39],"designed":[40],"reduce":[42],"data":[44],"dimensionality":[45,59],"improve":[47],"classification":[49,108],"accuracy":[50],"in":[51],"UNSW-NB15":[53],"dataset.":[54],"It":[55],"proposes":[56],"a":[57,96,180,184,189,193],"hybrid":[58],"reduction":[60],"system":[61,131],"that":[62,164],"does":[63],"feature":[64,68,156],"selection":[65],"(FS)":[66],"extraction":[69],"(FE).":[70],"FS":[71],"was":[72,83,110,132],"performed":[73],"using":[74,112,134],"Recursive":[76],"Feature":[77],"Elimination":[78],"(RFE)":[79],"technique,":[80],"while":[81],"FE":[82],"accomplished":[84],"by":[85],"transforming":[86],"into":[89,102],"principal":[90,161],"components.":[91,104],"This":[92],"combined":[93],"scheme":[94],"reduced":[95,165],"total":[97],"41":[99],"input":[100,203],"15":[103,160,200],"proposed":[106],"systems\u2019":[107],"performance":[109],"determined":[111],"an":[113],"ensemble":[114,151,207],"Support":[116],"Vector":[117],"Classifier":[118],"(SVC),":[119],"K-nearest":[120],"Neighbor":[121],"classifier":[122,128],"(KNC),":[123],"Deep":[125],"Neural":[126],"Network":[127],"(DNN).":[129],"evaluated":[133],"accuracy,":[135,179],"detection":[136,182],"rate,":[137,140,183,188],"false":[138,186],"positive":[139,187],"f1-score,":[141,191],"area":[143,195],"under":[144,196],"curve":[146,198],"metrics.":[147],"Comparing":[148],"voting":[150,206],"results":[152],"full":[155],"set":[157],"against":[158],"components":[162,201],"confirms":[163],"transformed":[167],"did":[169],"not":[170],"significantly":[171],"decrease":[172],"classifier\u2019s":[174],"performance.":[175],"We":[176],"achieved":[177],"94.34%":[178,194],"93.92%":[181],"5.23%":[185],"94.32%":[190],"when":[199],"were":[202],"classifier.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":2}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}
