Synthesises 312 peer-reviewed studies on machine-learning-based intrusion detection, adversarial attacks, and Large-Language-Model (LLM) hardening. Finds that deep-learning boosts detection precision by 14 pp but creates new attack surfaces; calls for explainable-AI and red-team benchmarks.
