Smart Security: Leveraging AI to Combat Emerging Cyber Threats

Abstract

A digital revolution has taken place and the landscape of cyber threats has expanded at a pace even faster than the ability of response based on traditional security system, thus an underlying requirement for dynamically smart and self-managing security systems remains! The paper describes how AI in general, and ML, DL and reinforcement learning (RL) in particular, is revolutionizing security through predictive real-time and context-aware threat management. "Today, with cloud, 5G and IoT architectures becoming more of a standard practice rather than an exception, traditional rule-based intrusion detection and static firewalls do not cut it in the fight against zero-day exploits or APTs let alone AI enabled cyber attacks.With analysis that covers 2019-2025, this finally concludes by questioning the effectiveness of AI in threat detection with Incident Response etc forensic investigation. Hybrid Model, the hybrid models that fusion of the ML-based anomaly detection with DL architectures (e.g. CNN–LSTM, Transformer-based) achieve over 98% for accuracy detection and Reinforcement Learning because they yield in more reinforcement to the self-optimizing defense strategy against new attack behavior.