The evolution of the cybersecurity defense driven by LLMs

The rapid advancement of large language models (LLMs) is fundamentally reshaping the architecture of cybersecurity defense systems. Traditional approaches are hindered by critical challenges, including the imbalance between attack and defense speed, high operational labor costs, and the ongoing trade-off between detection accuracy and false positives. Leveraging capabilities in natural language processing, multimodal reasoning, and agent-based orchestration, LLMs enable semantic-level threat understanding and dynamic adversarial simulations, transitioning cybersecurity paradigms from rule-based passive responses to cognition-driven proactive defense. This paper explores practical applications of LLMs in eight major security domains—including data protection, security operations, and email security—and outlines their role in the intelligent evolution of cybersecurity systems, while envisioning future transformations across the industry landscape.