Real-Time Anomaly Detection in IoT Networks Using Deep Neural Models
Detailed experimental evaluations demonstrate that deep neural models significantly outperform traditional machine learning approaches in terms of detection accuracy, false positive reduction, and scalability, and the suitability of deep learning-based anomaly detection systems for securing next-generation IoT networks while maintaining operational efficiency.