{"id":"https://openalex.org/W7117257436","doi":"https://doi.org/10.1109/jiot.2025.3648649","title":"Autonomous LLM Agent: A Memory-Augmented, Edge-Optimized SHAP Explanations With Zero-Day Attack Resilience in IoT/Industrial IoT Networks","display_name":"Autonomous LLM Agent: A Memory-Augmented, Edge-Optimized SHAP Explanations With Zero-Day Attack Resilience in IoT/Industrial IoT Networks","publication_year":2025,"publication_date":"2025-12-25","ids":{"openalex":"https://openalex.org/W7117257436","doi":"https://doi.org/10.1109/jiot.2025.3648649"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2025.3648649","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3648649","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/jiot.2025.3648649","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057218982","display_name":"Yakub Kayode Saheed","orcid":"https://orcid.org/0000-0002-0804-0707"},"institutions":[{"id":"https://openalex.org/I27765905","display_name":"North-West University","ror":"https://ror.org/010f1sq29","country_code":"ZA","type":"education","lineage":["https://openalex.org/I27765905"]}],"countries":["ZA"],"is_corresponding":true,"raw_author_name":"Yakub Kayode Saheed","raw_affiliation_strings":["Department of Information Systems, North-West University, Mahikeng, South Africa"],"affiliations":[{"raw_affiliation_string":"Department of Information Systems, North-West University, Mahikeng, South Africa","institution_ids":["https://openalex.org/I27765905"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115987055","display_name":"Chukwuere Joshua Ebere","orcid":null},"institutions":[{"id":"https://openalex.org/I27765905","display_name":"North-West University","ror":"https://ror.org/010f1sq29","country_code":"ZA","type":"education","lineage":["https://openalex.org/I27765905"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Joshua Ebere Chukwuere","raw_affiliation_strings":["Department of Information Systems, North-West University, Mahikeng, South Africa"],"affiliations":[{"raw_affiliation_string":"Department of Information Systems, North-West University, Mahikeng, South Africa","institution_ids":["https://openalex.org/I27765905"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5057218982"],"corresponding_institution_ids":["https://openalex.org/I27765905"],"apc_list":null,"apc_paid":null,"fwci":4.9367,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.95980915,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"13","issue":"7","first_page":"14213","last_page":"14228"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.28439998626708984,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.28439998626708984,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.1784999966621399,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.15690000355243683,"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/exploit","display_name":"Exploit","score":0.746999979019165},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5914999842643738},{"id":"https://openalex.org/keywords/attack-surface","display_name":"Attack surface","score":0.5841000080108643},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5529999732971191},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5180000066757202},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4959999918937683},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.48539999127388},{"id":"https://openalex.org/keywords/resilience","display_name":"Resilience (materials science)","score":0.4569999873638153},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.4187000095844269}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8382999897003174},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.746999979019165},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5914999842643738},{"id":"https://openalex.org/C2776576444","wikidata":"https://www.wikidata.org/wiki/Q303569","display_name":"Attack surface","level":2,"score":0.5841000080108643},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5529999732971191},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.5203999876976013},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5180000066757202},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4959999918937683},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.48539999127388},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.4569999873638153},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.4187000095844269},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40939998626708984},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3921000063419342},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.3817000091075897},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.3734999895095825},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3686000108718872},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35089999437332153},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.3165999948978424},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C2778505942","wikidata":"https://www.wikidata.org/wiki/Q18344624","display_name":"Microservices","level":3,"score":0.2906999886035919},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.28760001063346863},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.28299999237060547},{"id":"https://openalex.org/C2779119184","wikidata":"https://www.wikidata.org/wiki/Q294350","display_name":"ALARM","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C95922358","wikidata":"https://www.wikidata.org/wiki/Q5432725","display_name":"False positive rate","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C179768478","wikidata":"https://www.wikidata.org/wiki/Q1120057","display_name":"Cyber-physical system","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.2524000108242035},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2025.3648649","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3648649","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/jiot.2025.3648649","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3648649","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,226],"Internet":[1],"of":[2,38,60,141,159,202],"Things":[3],"(IoT),":[4],"particularly":[5],"its":[6,18],"industrial":[7],"subset":[8],"Industrial":[9],"IoT,":[10],"presents":[11],"a":[12,30,82,95,147,157,266],"critical":[13],"attack":[14],"surface":[15],"due":[16,183],"to":[17,107,118,184,193,221],"interconnected":[19],"nature.":[20],"As":[21],"emerging":[22],"threats":[23,121],"exploit":[24],"IoT":[25],"edge":[26,91,208],"networks,":[27],"there":[28],"is":[29],"growing":[31],"demand":[32],"for":[33,66,89,161,223],"anomaly":[34,86],"detection":[35,68,87],"systems":[36],"capable":[37],"addressing":[39],"zero-day":[40,73,120,162],"attacks":[41],"while":[42],"providing":[43],"explainable":[44,85],"predictions.":[45],"Existing":[46],"machine":[47],"learning":[48,52],"(ML)":[49],"and":[50,69,104,109,122,133,143,168,175,180,236,251,263],"deep":[51],"(DL)":[53],"methods":[54],"often":[55],"lack":[56],"explainability,":[57],"sensitivity,":[58],"absence":[59],"Large":[61],"Language":[62],"Model":[63],"(LLM)":[64],"agent":[65],"adaptive":[67],"struggle":[70],"with":[71,146,232],"unseen":[72],"threats.":[74],"Motivated":[75],"by":[76],"these":[77],"challenges,":[78],"we":[79],"introduce":[80],"Anomaly-Agent,":[81],"novel":[83],"LLM-powered":[84],"framework":[88],"IoT/IIoT":[90,272],"environments.":[92],"Anomaly-Agent":[93,116,128,177,242],"leverages":[94],"reasoning-followed-by-action":[96],"pipeline,":[97],"integrating":[98],"domain":[99],"tools,":[100],"external":[101],"knowledge":[102],"retrieval,":[103],"memory-augmented":[105],"decisions":[106],"detect":[108],"explain":[110],"anomalies.":[111],"Unlike":[112],"static":[113],"ML/DL":[114],"models,":[115],"adapts":[117],"evolving":[119],"supports":[123],"sensitivity":[124],"customization.":[125],"We":[126],"evaluated":[127],"on":[129,187,197],"the":[130],"Edge-IIoTset":[131],"(IIoT-specific)":[132],"CIC-IoT2023":[134],"(general":[135],"IoT)":[136],"datasets,":[137],"it":[138],"achieved":[139],"accuracies":[140],"0.96":[142],"0.89,":[144],"respectively,":[145],"false":[148],"alarm":[149],"rate":[150],"(FAR)":[151],"below":[152],"0.04.":[153],"It":[154,212],"also":[155,213],"attains":[156],"recall":[158],"0.65":[160],"attacks,":[163],"surpassing":[164],"traditional":[165],"ML":[166],"models":[167],"LLM":[169],"baselines":[170],"including":[171],"GPT-4o,":[172],"Claude":[173,181],"3.5,":[174],"GPT-4o-mini.":[176],"outperformed":[178],"GPT-4o":[179],"3.5":[182],"their":[185],"reliance":[186],"generic":[188],"prompting,":[189],"which":[190],"limits":[191],"performance":[192,228],"64%\u201370%":[194],"multi-class":[195,224],"F1-score":[196],"CIC-IoT2023.":[198],"Their":[199],"high":[200],"FAR":[201],"10%-13%":[203],"stems":[204],"from":[205,230],"misclassifying":[206],"benign":[207],"traffic":[209],"as":[210],"malicious.":[211],"surpasses":[214],"GPT-4o-mini,":[215],"where":[216],"token":[217],"constraints":[218],"reduce":[219],"accuracy":[220],"58%":[222],"tasks.":[225],"agent\u2019s":[227],"benefits":[229],"integration":[231],"SHAP,":[233],"enhancing":[234],"transparency":[235],"trust.":[237],"While":[238],"demonstrating":[239],"strong":[240],"performance,":[241],"faces":[243],"inherent":[244],"challenges":[245],"in":[246,248],"latency":[247],"complex":[249],"scenarios":[250],"adversarial":[252],"robustness":[253,262],"that":[254],"guide":[255],"future":[256],"improvements.":[257],"These":[258],"results":[259],"demonstrate":[260],"Anomaly-Agent\u2019s":[261],"interpretability,":[264],"offering":[265],"viable":[267],"path":[268],"toward":[269],"resilient,":[270],"LLM-driven":[271],"security":[273],"solutions.":[274]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-03-31T07:56:22.981413","created_date":"2025-12-25T00:00:00"}