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The document discusses the development of AI-driven intrusion detection systems (IDS) specifically designed for Internet of Things (IoT) networks, addressing significant security vulnerabilities posed by the proliferation of IoT devices. It reviews various machine learning techniques, including supervised, unsupervised, and reinforcement learning, assessing their effectiveness in real-time anomaly detection and the challenges faced in implementing these systems. The findings emphasize the need for a multi-l

Author

teachabd996

Language

EN