Internet of Thing
The Internet of Things (IoT) involves connecting billions of devices to collect and analyze data, aiming to improve efficiency and decision-making across various sectors. Current research heavily focuses on enhancing IoT security through machine learning (ML) models like deep neural networks (CNNs, LSTMs, Transformers), federated learning, and the integration of large language models (LLMs) for improved anomaly detection and attack prediction. These advancements are crucial for addressing the growing concerns of data privacy, security vulnerabilities, and resource constraints within increasingly complex IoT networks, impacting fields from smart cities to healthcare.
Papers
MalIoT: Scalable and Real-time Malware Traffic Detection for IoT Networks
Ethan Weitkamp, Yusuke Satani, Adam Omundsen, Jingwen Wang, Peilong Li
A Survey on Federated Learning for the Healthcare Metaverse: Concepts, Applications, Challenges, and Future Directions
Ali Kashif Bashir, Nancy Victor, Sweta Bhattacharya, Thien Huynh-The, Rajeswari Chengoden, Gokul Yenduri, Praveen Kumar Reddy Maddikunta, Quoc-Viet Pham, Thippa Reddy Gadekallu, Madhusanka Liyanage