Machine Learning-Based Intrusion Detection for Smart City Internet of Things Networks
This study investigates the effectiveness of supervised machine learning techniques for detecting cyberattacks in IoT-based smart city networks using the TON_IoT dataset, finding that advanced ensemble learning combined with robust feature engineering provides a reliable and scalable solution for securing smart city IoT networks.