Advanced Machine Learning for Cyber-Attack Detection in IoT Networks

1. Machine Learning for Cyber-Attack Detection in IoT Networks: An Overview2. Evaluation and Performance Metrics for IoT Security Networks3. Adversarial Machine Learning Techniques for the Industrial IoT Paradigm4. Federated Learning for Distributed Intrusion Detection in IoT Networks5. Safeguarding IoT Networks with Generative Adversarial Networks6. Meta-Learning for Cyber-Attack Detection in IoT Networks7. Transfer Learning with CNN for Cyberattack Detection in IoT Networks8. Lightweight Intrusion Detection Methods Based on Artificial Intelligence for IoT Networks9. A New Federated Learning System with Attention-Aware Aggregation Method for Intrusion Detection Systems10. Enhancing Intrusion Detection using Improved Sparrow Search Algorithm with Deep Learning on Internet of Things Environment11. Advancing Cyberattack Detection for In-Vehicle Network: A Comparative Study of Machine Learning-based Intrusion Detection System12. Practical Approaches Towards IoT Dataset Generation for Security Experiments13. Challenges and Potential Research Directions for Machine Learning-based Cyber-Attack Detection in IoT Networks