{"id":"https://openalex.org/W7202285099","doi":"https://doi.org/10.56201/ijcsmt.vol.12.no7.2026.pg1.27","title":"Hybrid Machine Learning Model for Real-Time Anomaly Detection in IOT Networks","display_name":"Hybrid Machine Learning Model for Real-Time Anomaly Detection in IOT Networks","publication_year":2026,"publication_date":"2026-08-12","ids":{"openalex":"https://openalex.org/W7202285099","doi":"https://doi.org/10.56201/ijcsmt.vol.12.no7.2026.pg1.27"},"language":"en","primary_location":{"id":"doi:10.56201/ijcsmt.vol.12.no7.2026.pg1.27","doi":"https://doi.org/10.56201/ijcsmt.vol.12.no7.2026.pg1.27","is_oa":true,"landing_page_url":"https://doi.org/10.56201/ijcsmt.vol.12.no7.2026.pg1.27","pdf_url":"https://www.iiardjournals.org/get/IJCSMT/VOL. 12 NO. 7 2026/HYBRID MACHINE LEARNING MODEL 1-27.pdf","source":{"id":"https://openalex.org/S4387282488","display_name":"INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND MATHEMATICAL THEORY E-ISSN","issn_l":"2545-5699","issn":["2545-5699","2695-1924"],"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":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Science and Mathematical Theory","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://www.iiardjournals.org/get/IJCSMT/VOL. 12 NO. 7 2026/HYBRID MACHINE LEARNING MODEL 1-27.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021935599","display_name":"Omega Sarjiyus","orcid":"https://orcid.org/0009-0002-7935-7733","observed_orcids":["https://orcid.org/0009-0002-7935-7733"]},"institutions":[{"id":"https://openalex.org/I106980716","display_name":"Adamawa State University","ror":"https://ror.org/01t11nq62","country_code":"NG","type":"education","lineage":["https://openalex.org/I106980716"]}],"countries":["NG"],"is_corresponding":true,"raw_author_name":"O. Sarjiyus","raw_affiliation_strings":["Department of Computer Science,   Adamawa State University Mubi-Nigeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science,   Adamawa State University Mubi-Nigeria","institution_ids":["https://openalex.org/I106980716"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5021935599"],"corresponding_institution_ids":["https://openalex.org/I106980716"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"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":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9965999722480774,"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":0.9965999722480774,"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":0.0017999999690800905,"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":0.00039999998989515007,"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/iot-security","display_name":"Internet of Things security","score":0.8050000071525574},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"anomaly detection","score":0.8610000014305115},{"id":"https://openalex.org/keywords/real-time-intrusion-detection","display_name":"real-time intrusion detection","score":0.765999972820282},{"id":"https://openalex.org/keywords/hybrid-machine-learning","display_name":"hybrid machine learning","score":0.8149999976158142},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.9710000157356262},{"id":"https://openalex.org/keywords/isolation-forest","display_name":"Isolation Forest","score":0.9710000157356262},{"id":"https://openalex.org/keywords/network-traffic-analysis","display_name":"network traffic analysis","score":0.6769999861717224},{"id":"https://openalex.org/keywords/false-alarm-reduction","display_name":"false alarm reduction","score":0.6959999799728394},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.5230000019073486}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6848000288009644},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6589000225067139},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6155999898910522},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6062999963760376},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5626000165939331},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5182999968528748},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.5110999941825867},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.5077000260353088},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.41449999809265137},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.4090000092983246},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.3865000009536743},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.38260000944137573},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.37720000743865967},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3312999904155731},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.29120001196861267},{"id":"https://openalex.org/C2775941552","wikidata":"https://www.wikidata.org/wiki/Q25212305","display_name":"Isolation (microbiology)","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2768999934196472},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2687999904155731},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.56201/ijcsmt.vol.12.no7.2026.pg1.27","doi":"https://doi.org/10.56201/ijcsmt.vol.12.no7.2026.pg1.27","is_oa":true,"landing_page_url":"https://doi.org/10.56201/ijcsmt.vol.12.no7.2026.pg1.27","pdf_url":"https://www.iiardjournals.org/get/IJCSMT/VOL. 12 NO. 7 2026/HYBRID MACHINE LEARNING MODEL 1-27.pdf","source":{"id":"https://openalex.org/S4387282488","display_name":"INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND MATHEMATICAL THEORY E-ISSN","issn_l":"2545-5699","issn":["2545-5699","2695-1924"],"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":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Science and Mathematical Theory","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.56201/ijcsmt.vol.12.no7.2026.pg1.27","doi":"https://doi.org/10.56201/ijcsmt.vol.12.no7.2026.pg1.27","is_oa":true,"landing_page_url":"https://doi.org/10.56201/ijcsmt.vol.12.no7.2026.pg1.27","pdf_url":"https://www.iiardjournals.org/get/IJCSMT/VOL. 12 NO. 7 2026/HYBRID MACHINE LEARNING MODEL 1-27.pdf","source":{"id":"https://openalex.org/S4387282488","display_name":"INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND MATHEMATICAL THEORY E-ISSN","issn_l":"2545-5699","issn":["2545-5699","2695-1924"],"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":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Science and Mathematical Theory","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7202285099.pdf","grobid_xml":"https://content.openalex.org/works/W7202285099.grobid-xml"},"referenced_works_count":67,"referenced_works":["https://openalex.org/W3198001643","https://openalex.org/W3200254765","https://openalex.org/W4238893454","https://openalex.org/W4295953946","https://openalex.org/W4319341361","https://openalex.org/W4371732540","https://openalex.org/W4378901629","https://openalex.org/W4380987383","https://openalex.org/W4384825299","https://openalex.org/W4385814617","https://openalex.org/W4388948083","https://openalex.org/W4389487930","https://openalex.org/W4390097426","https://openalex.org/W4391091696","https://openalex.org/W4391866717","https://openalex.org/W4394571622","https://openalex.org/W4396232472","https://openalex.org/W4399596087","https://openalex.org/W4401726558","https://openalex.org/W4401816616","https://openalex.org/W4402447701","https://openalex.org/W4402922510","https://openalex.org/W4402977745","https://openalex.org/W4403738747","https://openalex.org/W4404622240","https://openalex.org/W4405237468","https://openalex.org/W4405292220","https://openalex.org/W4405576390","https://openalex.org/W4405653153","https://openalex.org/W4405735633","https://openalex.org/W4405947842","https://openalex.org/W4405953171","https://openalex.org/W4406291624","https://openalex.org/W4406591335","https://openalex.org/W4406771786","https://openalex.org/W4406907824","https://openalex.org/W4407362917","https://openalex.org/W4407389004","https://openalex.org/W4408094869","https://openalex.org/W4408103891","https://openalex.org/W4408155247","https://openalex.org/W4408660318","https://openalex.org/W4408941305","https://openalex.org/W4409115955","https://openalex.org/W4409133392","https://openalex.org/W4409296638","https://openalex.org/W4409506545","https://openalex.org/W4410347235","https://openalex.org/W4410440153","https://openalex.org/W4410894032","https://openalex.org/W4411018006","https://openalex.org/W4411372854","https://openalex.org/W4411453100","https://openalex.org/W4411565930","https://openalex.org/W4411710505","https://openalex.org/W4411729646","https://openalex.org/W4412007118","https://openalex.org/W4412161741","https://openalex.org/W4412170828","https://openalex.org/W4412351612","https://openalex.org/W4412412322","https://openalex.org/W4412634477","https://openalex.org/W4412795792","https://openalex.org/W4414009738","https://openalex.org/W4414198799","https://openalex.org/W6946070054","https://openalex.org/W7162105945"],"related_works":["https://openalex.org/W4404578914","https://openalex.org/W4415018641","https://openalex.org/W7143490378","https://openalex.org/W7134175054","https://openalex.org/W4416396223","https://openalex.org/W4384648348","https://openalex.org/W7111389851","https://openalex.org/W7221234978","https://openalex.org/W4362498955","https://openalex.org/W7139931832"],"abstract_inverted_index":{"As":[0],"the":[1,18,39,45,68,102,142],"number":[2,28,233],"of":[3,5,20,23,29,36,47,70,104,132,182,185,188,193,234,241],"Internet":[4],"Things":[6],"devices":[7,31,43,75],"connected":[8,30],"continues":[9],"to":[10,44,53,64,77,80,84,91,118,121,135,170,201],"rise":[11],"rapidly,":[12],"a":[13,105,129],"negative":[14],"consequence":[15],"will":[16],"be":[17],"emergence":[19],"new":[21],"types":[22],"attack":[24],"vectors.":[25],"The":[26],"growing":[27],"generates":[32],"an":[33],"ever-increasing":[34],"volume":[35,69],"traffic":[37],"across":[38],"Internet,":[40],"exposing":[41],"these":[42],"threat":[46],"malicious":[48],"attacks.":[49],"Traditional":[50],"methods":[51],"used":[52],"identify":[54,122],"anomalous":[55,123],"behaviours":[56],"(for":[57],"example,":[58],"detecting":[59],"unusual":[60],"events)":[61],"are":[62],"unable":[63],"work":[65],"effectively":[66],"on":[67,110,150],"data":[71,95],"generated":[72],"by":[73,173],"IoT":[74],"due":[76],"their":[78,82,89],"sensitivity":[79],"noise,":[81],"tendency":[83],"have":[85],"class":[86],"imbalances,":[87],"and":[88,115,147,190,195,249],"inability":[90],"model":[92,108],"very":[93],"complex":[94],"patterns.":[96],"In":[97],"this":[98],"study,":[99],"we":[100],"propose":[101],"use":[103],"hybrid":[106,143,179],"machine-learning":[107],"based":[109],"Support":[111],"Vector":[112],"Machines":[113],"(SVM)":[114],"Isolation":[116,214],"Forest":[117,215],"enable":[119],"us":[120],"behaviour":[124],"in":[125,243,245],"real":[126],"time":[127],"with":[128,178,230],"higher":[130,239],"degree":[131],"accuracy":[133],"compared":[134],"using":[136,145,174,221],"either":[137],"method":[138],"independently.":[139],"We":[140],"implemented":[141],"approach":[144],"Python":[146],"tested":[148],"it":[149],"10,000":[151],"flow":[152],"records":[153],"created":[154],"from":[155],"actual":[156],"network":[157],"activity":[158],"(80%":[159],"for":[160,163,197],"training,":[161],"20%":[162],"testing).":[164],"Hybrid":[165,198],"Algorithm":[166,216],"Results":[167],"were":[168],"superior":[169],"results":[171],"achieved":[172],"each":[175],"algorithm":[176],"alone,":[177],"achieving":[180],"Accuracy":[181],"98.3%,":[183],"Precision":[184],"98.0%,":[186],"Sensitivity":[187],"98.5%,":[189],"F1":[191],"Score":[192],"98.2%,":[194],"AUC":[196,210],"was":[199],"equal":[200],"0.99,":[202],"which":[203],"is":[204],"greater":[205],"than":[206],"SVM":[207],"alone":[208,217],"(94.2%,":[209],"=":[211],"0.96)":[212],"or":[213],"(91.5%,":[218],"93),":[219],"Therefore,":[220],"complementary":[222],"algorithms":[223],"combined":[224],"provide":[225],"significantly":[226],"improved":[227],"detection":[228],"rate":[229],"greatly":[231],"reduced":[232],"false":[235],"alerts,":[236],"thus":[237],"providing":[238],"level":[240],"confidence":[242],"deploying":[244],"healthcare,":[246],"industrial":[247],"automation":[248],"smart":[250],"cities.":[251]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-08-13T00:00:00"}
