AI-POWERED INTRUSION DETECTION SYSTEM FOR IOT SECURITY

Abstract-The increasing use of IoT devices has led to growing cybersecurity threats, making traditional Intrusion Detection Systems (IDS) ineffective against evolving attacks. This project proposes an AI-powered IDS that integrates Machine Learning (ML), Deep Learning (DL), and Blockchain to detect and prevent cyber threats in real time. The system employs CNN, LSTM, and Isolation Forest for anomaly detection, Neuromorphic Computing (SNNs) for fast processing, and Blockchain for secure logging. Additionally, Reinforcement Learning (RL) enables autonomous security adaptation. The proposed system enhances IoT security, real-time threat detection, and self-healing capabilities, making it a robust solution for modern cyber challenges.