{"id":"https://openalex.org/W7220389347","doi":"https://doi.org/10.3389/frai.2026.1932015","title":"Optimizing multi-class intrusion detection in IIoT: advanced feature selection using grey wolf optimizer and machine learning classifiers","display_name":"Optimizing multi-class intrusion detection in IIoT: advanced feature selection using grey wolf optimizer and machine learning classifiers","publication_year":2026,"publication_date":"2026-10-05","ids":{"openalex":"https://openalex.org/W7220389347","doi":"https://doi.org/10.3389/frai.2026.1932015","pmid":"https://pubmed.ncbi.nlm.nih.gov/42898504","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/13677896"},"language":"en","primary_location":{"id":"doi:10.3389/frai.2026.1932015","doi":"https://doi.org/10.3389/frai.2026.1932015","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2026.1932015","pdf_url":"https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2026.1932015/pdf","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2026.1932015/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136789016","display_name":"Ibrahim Al-Shibly","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I251424209","display_name":"Universitat de Girona","ror":"https://ror.org/01xdxns91","country_code":"ES","type":"education","lineage":["https://openalex.org/I251424209"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Ibrahim Al-Shibly","raw_affiliation_strings":["Universitat de Girona - Control Engineering and Intelligent Systems, Campus Montilivi, EPS IV"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitat de Girona - Control Engineering and Intelligent Systems, Campus Montilivi, EPS IV","institution_ids":["https://openalex.org/I251424209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045078615","display_name":"Lloren\u00e7 Burgas","orcid":"https://orcid.org/0000-0002-5677-7594","observed_orcids":["https://orcid.org/0000-0002-5677-7594"]},"institutions":[{"id":"https://openalex.org/I251424209","display_name":"Universitat de Girona","ror":"https://ror.org/01xdxns91","country_code":"ES","type":"education","lineage":["https://openalex.org/I251424209"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Lloren\u00e7 Burgas","raw_affiliation_strings":["Universitat de Girona - Control Engineering and Intelligent Systems, Campus Montilivi, EPS IV"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitat de Girona - Control Engineering and Intelligent Systems, Campus Montilivi, EPS IV","institution_ids":["https://openalex.org/I251424209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102954188","display_name":"Joaquim Massana","orcid":"https://orcid.org/0000-0003-3609-0688","observed_orcids":["https://orcid.org/0000-0003-3609-0688"]},"institutions":[{"id":"https://openalex.org/I251424209","display_name":"Universitat de Girona","ror":"https://ror.org/01xdxns91","country_code":"ES","type":"education","lineage":["https://openalex.org/I251424209"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Joaquim Massana","raw_affiliation_strings":["Universitat de Girona - Control Engineering and Intelligent Systems, Campus Montilivi, EPS IV"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitat de Girona - Control Engineering and Intelligent Systems, Campus Montilivi, EPS IV","institution_ids":["https://openalex.org/I251424209"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5136789016"],"corresponding_institution_ids":["https://openalex.org/I251424209"],"apc_list":{"value":1950,"currency":"CHF","value_usd":2353},"apc_paid":{"value":1950,"currency":"CHF","value_usd":2353},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.72313551,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":null,"first_page":"1932015","last_page":"1932015"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9970999956130981,"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":0.9970999956130981,"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/T12391","display_name":"Artificial Immune Systems Applications","score":0.0006000000284984708,"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/T12326","display_name":"Network Packet Processing and Optimization","score":0.00019999999494757503,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/industrial-internet-of-things","display_name":"Industrial Internet of Things","score":0.7850000262260437},{"id":"https://openalex.org/keywords/intrusion-detection","display_name":"intrusion detection","score":0.9419999718666077},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"multi-class classification","score":0.9079999923706055},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.9520000219345093},{"id":"https://openalex.org/keywords/grey-wolf-optimizer","display_name":"grey wolf optimizer","score":0.8629999756813049},{"id":"https://openalex.org/keywords/edge-iiotset","display_name":"Edge-IIoTset","score":0.9769999980926514},{"id":"https://openalex.org/keywords/industrial-cybersecurity","display_name":"industrial cybersecurity","score":0.421999990940094}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6995999813079834},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6740000247955322},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6685000061988831},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6499999761581421},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.642799973487854},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6028000116348267},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.5724999904632568},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.512499988079071},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5062999725341797},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43130001425743103},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4106000065803528},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.3456999957561493},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3280999958515167},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C158251709","wikidata":"https://www.wikidata.org/wiki/Q354025","display_name":"Intrusion","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C2776839635","wikidata":"https://www.wikidata.org/wiki/Q14942679","display_name":"Random tree","level":4,"score":0.27079999446868896},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.2531000077724457}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/frai.2026.1932015","doi":"https://doi.org/10.3389/frai.2026.1932015","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2026.1932015","pdf_url":"https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2026.1932015/pdf","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13677896","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13677896/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13677896/pdf/frai-09-1932015.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Front Artif Intell","raw_type":"Text"},{"id":"pmid:42898504","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42898504","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in artificial intelligence","raw_type":"Journal Article"},{"id":"pmh:oai:doaj.org/article:f1526ef993ab4b838744332b710b5485","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/f1526ef993ab4b838744332b710b5485","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,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Artificial Intelligence, Vol 9 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/frai.2026.1932015","doi":"https://doi.org/10.3389/frai.2026.1932015","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2026.1932015","pdf_url":"https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2026.1932015/pdf","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5378999710083008}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7220389347.pdf","grobid_xml":"https://content.openalex.org/works/W7220389347.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1678356000","https://openalex.org/W2061438946","https://openalex.org/W2156665896","https://openalex.org/W2903950532","https://openalex.org/W2911964244","https://openalex.org/W3036517673","https://openalex.org/W4226319939","https://openalex.org/W4391436933","https://openalex.org/W4392120324","https://openalex.org/W4393065931","https://openalex.org/W4399392488","https://openalex.org/W4400187742","https://openalex.org/W4400251673","https://openalex.org/W4401056366","https://openalex.org/W4401729226","https://openalex.org/W4402130526","https://openalex.org/W4404725737","https://openalex.org/W4407052789","https://openalex.org/W4408410698","https://openalex.org/W4408793049","https://openalex.org/W4410287398","https://openalex.org/W4411047030","https://openalex.org/W4411604510","https://openalex.org/W4411870410","https://openalex.org/W4411957384","https://openalex.org/W4412939694","https://openalex.org/W4414205827","https://openalex.org/W4414655439","https://openalex.org/W4415359185","https://openalex.org/W4416208996","https://openalex.org/W4416455036","https://openalex.org/W7104073568","https://openalex.org/W7172537203"],"related_works":["https://openalex.org/W4406354159","https://openalex.org/W7135067554","https://openalex.org/W4414198000","https://openalex.org/W4320925565","https://openalex.org/W4414194857","https://openalex.org/W7162118366","https://openalex.org/W7160330870","https://openalex.org/W7162685874","https://openalex.org/W3189826552","https://openalex.org/W7118128109"],"abstract_inverted_index":{"Introduction":[0],"The":[1,65],"rapid":[2],"expansion":[3],"of":[4,8,16,108],"the":[5,13,70,123,197],"Industrial":[6],"Internet":[7],"Things":[9],"(IIoT)":[10],"has":[11],"increased":[12],"cyberattack":[14],"surface":[15],"industrial":[17],"infrastructures,":[18],"creating":[19],"demand":[20],"for":[21,46,212],"intrusion":[22,49,215],"detection":[23,50],"systems":[24],"(IDS)":[25],"that":[26,189],"combine":[27],"predictive":[28,179,205],"performance":[29],"with":[30],"deployment":[31],"efficiency.":[32],"Methods":[33],"This":[34],"study":[35],"proposes":[36],"a":[37,81,201],"Grey":[38],"Wolf":[39],"Optimizer":[40],"(GWO)-guided":[41],"fixed":[42],"top-k":[43],"feature-ranking":[44],"framework":[45,66,199],"multi-class":[47],"IIoT":[48,72,96,214],"using":[51,113],"candidate-dependent":[52],"redundancy":[53,173],"regularization,":[54,176],"class-weighted":[55],"learning,":[56],"stratified":[57],"cross-validation,":[58],"repeated":[59],"runs,":[60],"and":[61,75,89,101,110,138,155,209],"independent":[62],"holdout":[63,105],"evaluation.":[64],"was":[67,181],"evaluated":[68],"on":[69,78,186],"CIC":[71,95],"Dataset":[73,97],"2025":[74],"independently":[76],"assessed":[77],"Edge-IIoTset":[79,187],"as":[80],"secondary":[82],"benchmark":[83],"across":[84],"six":[85],"machine":[86],"learning":[87],"classifiers":[88],"several":[90],"feature-selection":[91,190],"baselines.":[92],"Results":[93,185],"On":[94],"2025,":[98],"Random":[99],"Forest":[100],"Decision":[102],"Tree":[103],"achieved":[104],"Macro-F1":[106],"scores":[107],"0.9389":[109],"0.9330,":[111],"respectively,":[112],"only":[114],"10":[115],"selected":[116],"features,":[117],"representing":[118],"an":[119],"85.92%":[120],"reduction":[121],"from":[122,165],"71-feature":[124],"model-input":[125],"space.":[126],"Repeated":[127],"training-only":[128],"comparisons":[129],"showed":[130,170,188],"significant":[131],"overall":[132],"differences":[133],"among":[134],"GWO,":[135],"BA,":[136],"LightGBM,":[137],"Boruta":[139],"(Friedman":[140],"\u03c7":[141],"\u00b2":[142],"=":[143,146,150],"16.920,":[144],"p":[145],"0.000734;":[147],"Kendall\u2019s":[148],"W":[149],"0.564);":[151],"GWO":[152],"outperformed":[153],"BA":[154],"LightGBM":[156],"after":[157],"Holm":[158],"correction":[159],"but":[160],"did":[161],"not":[162,182],"differ":[163],"significantly":[164],"Boruta.":[166],"Ablation":[167],"analysis":[168],"further":[169],"lower":[171],"feature":[172,207],"under":[174],"adaptive":[175],"although":[177],"its":[178],"advantage":[180],"statistically":[183],"significant.":[184],"effectiveness":[191],"is":[192],"dataset":[193],"dependent.":[194],"Discussion":[195],"Overall,":[196],"proposed":[198],"provides":[200],"practical":[202],"balance":[203],"between":[204],"performance,":[206],"compactness,":[208],"computational":[210],"efficiency":[211],"resource-constrained":[213],"detection.":[216]},"counts_by_year":[],"updated_date":"2026-10-29T09:56:32.521200","created_date":"2026-10-06T00:00:00"}
