{"id":"https://openalex.org/W7152521631","doi":"https://doi.org/10.1109/icecet63943.2025.11472081","title":"A Comparative Analysis of Machine Learning Models for Intrusion Detection in IoT Networks","display_name":"A Comparative Analysis of Machine Learning Models for Intrusion Detection in IoT Networks","publication_year":2025,"publication_date":"2025-07-03","ids":{"openalex":"https://openalex.org/W7152521631","doi":"https://doi.org/10.1109/icecet63943.2025.11472081"},"language":null,"primary_location":{"id":"doi:10.1109/icecet63943.2025.11472081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icecet63943.2025.11472081","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 5th International Conference on Electrical, Computer and Energy Technologies (ICECET)","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/A5120623093","display_name":"Merve Nur Candan","orcid":"https://orcid.org/0009-0003-3182-8919"},"institutions":[{"id":"https://openalex.org/I41641357","display_name":"Ege University","ror":"https://ror.org/02eaafc18","country_code":"TR","type":"education","lineage":["https://openalex.org/I41641357"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Merve Candan","raw_affiliation_strings":["Ege University,Graduate School of Natural and Applied Sciences,Bornova-Izmir,Turkiye,35100"],"affiliations":[{"raw_affiliation_string":"Ege University,Graduate School of Natural and Applied Sciences,Bornova-Izmir,Turkiye,35100","institution_ids":["https://openalex.org/I41641357"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5133279149","display_name":"Ozgu Can","orcid":null},"institutions":[{"id":"https://openalex.org/I41641357","display_name":"Ege University","ror":"https://ror.org/02eaafc18","country_code":"TR","type":"education","lineage":["https://openalex.org/I41641357"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Ozgu Can","raw_affiliation_strings":["Ege University,Department of Computer Engineering,Bornova-Izmir,Turkiye,35100"],"affiliations":[{"raw_affiliation_string":"Ege University,Department of Computer Engineering,Bornova-Izmir,Turkiye,35100","institution_ids":["https://openalex.org/I41641357"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5120623093"],"corresponding_institution_ids":["https://openalex.org/I41641357"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.78247903,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.684499979019165,"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":0.684499979019165,"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/T13038","display_name":"Internet of Things and AI","score":0.0215000007301569,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.013100000098347664,"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/internet-of-things","display_name":"Internet of Things","score":0.48510000109672546},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.48170000314712524},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3619000017642975},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.32910001277923584},{"id":"https://openalex.org/keywords/intrusion","display_name":"Intrusion","score":0.30000001192092896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6309999823570251},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5400999784469604},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.48510000109672546},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.48170000314712524},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4772999882698059},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3619000017642975},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32910001277923584},{"id":"https://openalex.org/C158251709","wikidata":"https://www.wikidata.org/wiki/Q354025","display_name":"Intrusion","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29980000853538513},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2574000060558319}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icecet63943.2025.11472081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icecet63943.2025.11472081","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 5th International Conference on Electrical, Computer and Energy Technologies (ICECET)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2911505293","https://openalex.org/W2991140181","https://openalex.org/W3000307855","https://openalex.org/W3091379954","https://openalex.org/W4388573952","https://openalex.org/W4392694748","https://openalex.org/W4393115034","https://openalex.org/W4394965522","https://openalex.org/W4396532891"],"related_works":[],"abstract_inverted_index":{"The":[0,165,207],"widespread":[1],"adoption":[2],"of":[3,5,23,35,46,115,128,204,209,247],"Internet":[4],"Things":[6],"(IoT)":[7],"devices":[8,25],"across":[9],"various":[10,116],"domains":[11],"has":[12],"significantly":[13],"enhanced":[14],"connectivity":[15],"and":[16,44,69,81,105,140,150,152,162,183,188],"automation.":[17],"However,":[18,72],"the":[19,33,42,122,126,170,178,245],"inherent":[20],"security":[21,34],"vulnerabilities":[22],"these":[24,229],"make":[26],"them":[27],"prime":[28],"targets":[29],"for":[30,41,98,119,215,224,235],"cyberattacks.":[31],"Ensuring":[32],"IoT":[36,86,226,248],"ecosystems":[37,249],"necessitates":[38],"robust":[39],"mechanisms":[40],"detection":[43],"prevention":[45],"malicious":[47],"activities.":[48],"Intrusion":[49],"Detection":[50],"Systems":[51],"(IDS)":[52],"play":[53],"a":[54,95,112,233],"crucial":[55],"role":[56],"in":[57,85,202,218],"this":[58,210],"regard":[59],"by":[60,102],"ceaselessly":[61],"tracking":[62],"network":[63],"traffic":[64],"to":[65,78,243],"identify":[66],"anomalous":[67],"behavior":[68],"potential":[70],"threats.":[71,253],"conventional":[73],"IDS":[74,100,120,222,241],"approaches":[75],"often":[76],"struggle":[77],"detect":[79],"sophisticated":[80],"evolving":[82],"attack":[83],"patterns":[84],"environments.":[87],"Machine":[88],"learning":[89],"(ML)":[90],"techniques":[91],"have":[92],"emerged":[93],"as":[94,232],"promising":[96],"solution":[97],"enhancing":[99],"capabilities":[101],"enabling":[103],"adaptive":[104],"data-driven":[106],"threat":[107],"detection.":[108],"This":[109],"study":[110,211],"conducts":[111],"comprehensive":[113],"evaluation":[114],"ML":[117],"algorithms":[118],"using":[121,158],"RT-IoT2022":[123],"dataset.":[124],"Specifically,":[125],"performance":[127,155],"Random":[129,186],"Forest,":[130],"Decision":[131,189],"Tree,":[132],"K-Nearest":[133],"Neighbors":[134],"(KNN),":[135],"Logistic":[136],"Regression,":[137],"Naive":[138],"Bayes,":[139],"Gradient":[141,171],"Boosting":[142,172],"classifiers":[143],"is":[144,156],"assessed.":[145],"These":[146],"models":[147,191],"are":[148],"trained":[149],"tested,":[151],"their":[153],"classification":[154,195],"evaluated":[157],"accuracy,":[159,180],"precision,":[160,181],"recall,":[161,182],"F1-score":[163],"metrics.":[164],"experimental":[166],"findings":[167,230],"indicate":[168],"that":[169],"algorithm":[173],"outperforms":[174],"other":[175],"models,":[176],"achieving":[177],"highest":[179],"F1-score.":[184],"While":[185],"Forest":[187],"Tree":[190],"also":[192],"demonstrate":[193],"strong":[194],"performance,":[196],"they":[197],"exhibit":[198],"higher":[199],"computational":[200],"costs":[201],"terms":[203],"processing":[205],"time.":[206],"results":[208],"provide":[212],"valuable":[213],"insights":[214],"cybersecurity":[216],"practitioners":[217],"selecting":[219],"suitable":[220],"ML-based":[221],"solutions":[223],"securing":[225],"networks.":[227],"Furthermore,":[228],"serve":[231],"foundation":[234],"future":[236],"research":[237],"aimed":[238],"at":[239],"optimizing":[240],"frameworks":[242],"enhance":[244],"resilience":[246],"against":[250],"emerging":[251],"cyber":[252]},"counts_by_year":[],"updated_date":"2026-04-11T06:13:24.991567","created_date":"2026-04-10T00:00:00"}