Next-Generation Cybersecurity: A Deep Survey of AI and Soft Computing Techniques for Autonomous and Explainable Defense Systems

Abstract

The complexity of cyber threats has escalated beyond the capabilities of static security systems, pushing the evolution of defense mechanisms toward intelligent, adaptive paradigms. This survey presents a systematic and in-depth review of advanced cybersecurity approaches developed between 2023 and 2025 using artificial intelligence (AI) and soft computing. We critically classify and analyze recent innovations in machine learning, deep learning, fuzzy logic, evolutionary computation, and hybrid models. Furthermore, we highlight the role of explainable AI (XAI), zero-shot learning, generative adversarial defense, and federated systems. The survey outlines key trends, benchmarks, and open research challenges, and proposes a novel taxonomy for future directions toward trustworthy, real-time, and autonomous cybersecurity frameworks.