IoT Traffic

Internet of Things (IoT) traffic analysis focuses on understanding and managing the diverse network communications generated by interconnected devices. Current research emphasizes developing accurate and efficient methods for classifying this traffic, often employing deep learning architectures like transformers and time-distributed networks, to improve network security, resource allocation, and quality of service. This work is crucial for addressing security threats like botnets and DDoS attacks, as well as enabling effective anomaly detection and user privacy protection in increasingly complex IoT ecosystems. The development of robust and adaptable models is paramount given the inherent variability and concept drift in IoT traffic patterns.