Advanced Machine Learning for Cyber-Attack Detection in IoT Networks

1. Machine Learning for Cyber-Attack Detection in IoT Networks: An Overview<br>2. Evaluation and Performance Metrics for IoT Security Networks<br>3. Adversarial Machine Learning Techniques for the Industrial IoT Paradigm<br>4. Federated Learning for Distributed Intrusion Detection in IoT Networks<br>5. Safeguarding IoT Networks with Generative Adversarial Networks<br>6. Meta-Learning for Cyber-Attack Detection in IoT Networks<br>7. Transfer Learning with CNN for Cyberattack Detection in IoT Networks<br>8. Lightweight Intrusion Detection Methods Based on Artificial Intelligence for IoT Networks<br>9. A New Federated Learning System with Attention-Aware Aggregation Method for Intrusion Detection Systems<br>10. Enhancing Intrusion Detection using Improved Sparrow Search Algorithm with Deep Learning on Internet of Things Environment<br>11. Advancing Cyberattack Detection for In-Vehicle Network: A Comparative Study of Machine Learning-based Intrusion Detection System<br>12. Practical Approaches Towards IoT Dataset Generation for Security Experiments<br>13. Challenges and Potential Research Directions for Machine Learning-based Cyber-Attack Detection in IoT Networks