Intelligent Systems with Applications · 2023 · 50 citations · 29 references
ComputingComputer EngineeringComputer ScienceComputer SecurityEdge ComputingInternet Of ThingsEdge Artificial IntelligenceEdge SecurityIndustrial Internet Of ThingsIntrusion DetectionIot SecurityThreat DetectionComparative EvaluationIndustrial Iot ApplicationsIndustrial Iot PlatformsIntrusion ClassificationIntrusion Detection For Industrial NetworksIot Intrusion DetectionMachine Learning For Intrusion DetectionNetwork Intrusion Detection
We propose and evaluate a data-driven intrusion detection system (IDS) for the Internet of Things (IoT) and Industrial IoT (IIoT) environments using the Edge-IIoT-2022 dataset. We model the IDS problem as a classification problem and learn the classifier via supervised learning algorithms. Our main contribution is an empirical analysis and evaluation of the Edge-IIoT-2022 dataset, which is a recent dataset compiled for developing IDSs in IoT and IIoT environments. We develop several IDSs from standard data analytics algorithms and evaluate their performance on Edge-IIoT-2022. We compare our IDSs with prior arts and demonstrate that highly accurate binary-class IDSs can be built via Edge-IIoT-2022, whereas multi-class IDSs would require careful treatment.
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