A Multi-Dimensional Evaluation Framework for IoT Intrusion Detection: Balancing Accuracy, Efficiency and Real-World Deployment Constraints

The rapid proliferation of Internet of Things (IoT) devices has introduced unprecedented security vulnerabilities, with botnet attacks representing persistent threats to network infrastructure. While machine learning-based intrusion detection systems (IDS) show promise in laboratory settings, real-world deployment faces challenges including extreme class imbalance, resource constraints, and false alarm minimization. Traditional evaluation approaches focus primarily on accuracy, overlooking deplo