{"id":"https://openalex.org/W4391248693","doi":"https://doi.org/10.1109/access.2024.3359033","title":"A Comparative Study of Anomaly Detection Techniques for IoT Security Using Adaptive Machine Learning for IoT Threats","display_name":"A Comparative Study of Anomaly Detection Techniques for IoT Security Using Adaptive Machine Learning for IoT Threats","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4391248693","doi":"https://doi.org/10.1109/access.2024.3359033"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3359033","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3359033","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10415174.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10415174.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081643142","display_name":"Dheyaaldin Alsalman","orcid":"https://orcid.org/0000-0002-8493-2758"},"institutions":[{"id":"https://openalex.org/I3132564352","display_name":"Dar Al-Hekma University","ror":"https://ror.org/01g0jya04","country_code":"SA","type":"education","lineage":["https://openalex.org/I3132564352"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Dheyaaldin Alsalman","raw_affiliation_strings":["Department of Cybersecurity, School of Engineering, Computing and Design, Dar Al-Hekma University, Jeddah, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-8493-2758","affiliations":[{"raw_affiliation_string":"Department of Cybersecurity, School of Engineering, Computing and Design, Dar Al-Hekma University, Jeddah, Saudi Arabia","institution_ids":["https://openalex.org/I3132564352"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5081643142"],"corresponding_institution_ids":["https://openalex.org/I3132564352"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":22.0379,"has_fulltext":true,"cited_by_count":78,"citation_normalized_percentile":{"value":0.99603222,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"12","issue":null,"first_page":"14719","last_page":"14730"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9965000152587891,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.972599983215332,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8278267979621887},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7556928396224976},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6584877967834473},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6013516783714294},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5889177322387695},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5352659225463867},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5247012376785278},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.48177191615104675},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4771544337272644},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4401487112045288},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.22210589051246643}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8278267979621887},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7556928396224976},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6584877967834473},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6013516783714294},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5889177322387695},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5352659225463867},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5247012376785278},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.48177191615104675},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4771544337272644},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4401487112045288},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.22210589051246643},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3359033","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3359033","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10415174.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:52cf265d8e9c4279bb5505e4914600c3","is_oa":true,"landing_page_url":"https://doaj.org/article/52cf265d8e9c4279bb5505e4914600c3","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":"IEEE Access, Vol 12, Pp 14719-14730 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3359033","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3359033","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10415174.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391248693.pdf","grobid_xml":"https://content.openalex.org/works/W4391248693.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W2699854166","https://openalex.org/W2996143878","https://openalex.org/W3033675321","https://openalex.org/W3087990969","https://openalex.org/W3110885177","https://openalex.org/W3111288713","https://openalex.org/W3135584216","https://openalex.org/W3137923936","https://openalex.org/W3169598894","https://openalex.org/W3183530150","https://openalex.org/W3205446974","https://openalex.org/W3213173707","https://openalex.org/W4205737724","https://openalex.org/W4223612401","https://openalex.org/W4292523197","https://openalex.org/W4304183900","https://openalex.org/W4307868829","https://openalex.org/W4310147657","https://openalex.org/W4310353354","https://openalex.org/W4353046955","https://openalex.org/W4376644501","https://openalex.org/W4385462766","https://openalex.org/W4386070139","https://openalex.org/W4386386840"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4377864969","https://openalex.org/W3030345572"],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,157,185],"is":[2,186],"a":[3,152],"critical":[4],"aspect":[5],"of":[6,29,54,103,117,127,149,174],"various":[7],"applications,":[8],"including":[9,84],"security,":[10,177],"healthcare,":[11,178],"and":[12,42,61,73,76,87,107,119,158,179],"network":[13],"monitoring.":[14],"In":[15],"this":[16],"study,":[17],"we":[18],"introduce":[19],"FusionNet,":[20],"an":[21,115,125],"innovative":[22],"ensemble":[23],"model":[24,154],"that":[25,92],"combines":[26],"the":[27,52,147,171],"strengths":[28],"multiple":[30],"machine":[31,81],"learning":[32,82],"algorithms,":[33],"namely":[34],"Random":[35],"Forest,":[36],"K-Nearest":[37],"Neighbors,":[38],"Support":[39],"Vector":[40],"Machine,":[41],"Multi-Layer":[43],"Perceptron,":[44],"for":[45,141,155],"enhanced":[46],"anomaly":[47,156,184],"detection.":[48],"FusionNet\u2019s":[49,65,129],"architecture":[50],"leverages":[51],"diversity":[53],"these":[55,96],"algorithms":[56],"to":[57,132],"achieve":[58],"high":[59],"accuracy":[60,116,126,137],"precision.":[62],"We":[63],"evaluate":[64],"performance":[66,164],"on":[67,120],"two":[68],"distinct":[69],"datasets,":[70],"Dataset":[71,74,111,121],"1":[72],"2,":[75,122],"compare":[77],"it":[78,123],"with":[79,135],"traditional":[80,166],"models,":[83],"SVM,":[85],"KNN,":[86],"RF.":[88],"The":[89,168],"results":[90,169],"demonstrate":[91],"FusionNet":[93,113,150,175],"consistently":[94],"outperforms":[95],"models":[97],"across":[98],"both":[99],"datasets":[100],"in":[101,176],"terms":[102],"accuracy,":[104],"precision,":[105],"recall,":[106],"F1":[108],"score.":[109],"On":[110],"1,":[112],"achieves":[114],"98.5%":[118],"attains":[124],"99.5%.":[128],"remarkable":[130],"ability":[131],"detect":[133],"anomalies":[134],"exceptional":[136],"underscores":[138],"its":[139,162],"potential":[140],"real-world":[142],"applications.":[143],"This":[144],"study":[145],"highlights":[146],"significance":[148],"as":[151],"robust":[153],"provides":[159],"insights":[160],"into":[161],"superior":[163],"over":[165],"models.":[167],"emphasize":[170],"promising":[172],"prospects":[173],"other":[180],"domains":[181],"where":[182],"accurate":[183],"crucial.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":16},{"year":2025,"cited_by_count":46},{"year":2024,"cited_by_count":16}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}
