Research on Internet of Things Monitoring and Defense Technology Based on Artificial Intelligence

As the Internet of Things (IoT) is widely used in smart campuses of higher education institutions, the heterogeneity of devices, resource limitations and complexity of security threats have become urgent issues to be addressed. In this research, an IoT monitoring and defence technology solution that integrates edge AI and deep learning is proposed for a specific higher education institution. By constructing a hybrid model that combines a multilayer perceptron (MLP) and a convolutional neural network (CNN), anomalous traffic is detected with 98.7% accuracy. A lightweight encryption protocol aims to reduce device power consumption by 30%. A dynamic defensive rule engine is developed with a response latency of less than 50ms. The experiment is validated using the CIC IoT 2022 dataset, which shows that the system outperforms traditional solutions in DDoS attack detection and side-channel attack defence, providing a reusable technology path for IoT security in education.