Cybersecurity demands rigorous and scalable techniques to ensure system correctness, robustness, and resilience against evolving threats. Automated reasoning, encompassing formal logic, theorem proving, model checking, and symbolic analysis, provides a foundational framework for verifying security properties across diverse domains such as access control, protocol design, vulnerability detection, and adversarial modeling. This survey presents a comprehensive overview of the role of automated reasoning in cybersecurity, analyzing how logical systems, including temporal, deontic, and epistemic logics are employed to formalize and verify security guarantees. We examine SOTA tools and frameworks, explore integrations with AI for neural-symbolic reasoning, and highlight critical research gaps, particularly in scalability, compositionality, and multi-layered security modeling. The paper concludes with a set of well-grounded future research directions, aiming to foster the development of secure systems through formal, automated, and explainable reasoning techniques.

翻译：网络安全需要严格且可扩展的技术来确保系统在面对不断演变的威胁时具备正确性、鲁棒性和弹性。自动推理——涵盖形式逻辑、定理证明、模型检测和符号分析——为验证跨不同领域（如访问控制、协议设计、漏洞检测和对抗建模）的安全属性提供了一个基础性框架。本综述全面概述了自动推理在网络安全中的作用，分析了包括时态逻辑、道义逻辑和认知逻辑在内的逻辑系统如何被用于形式化和验证安全保证。我们考察了最先进的工具与框架，探索了与人工智能在神经符号推理方面的集成，并强调了关键的研究空白，特别是在可扩展性、组合性以及多层安全建模方面。本文最后提出了一系列有充分依据的未来研究方向，旨在通过形式化、自动化且可解释的推理技术促进安全系统的开发。