Cyber warfare has become a central element of modern conflict, especially within multi-domain operations. As both a distinct and critical domain, cyber warfare requires integrating defensive and offensive technologies into coherent strategies. While prior research has emphasized isolated tactics or fragmented technologies, a holistic understanding is essential for effective resource deployment and risk mitigation. Game theory offers a unifying framework for this purpose. It not only models attacker-defender interactions but also provides quantitative tools for equilibrium analysis, risk assessment, and strategic reasoning. Integrated with modern AI techniques, game-theoretic models enable the design and optimization of strategies across multiple levels of cyber warfare, from policy and strategy to operations, tactics, and technical implementations. These models capture the paradoxical logic of conflict, where more resources do not always translate into greater advantage, and where nonlinear dynamics govern outcomes. To illustrate the approach, this chapter examines RedCyber, a synthetic cyber conflict, demonstrating how game-theoretic methods capture the interdependencies of cyber operations. The chapter concludes with directions for future research on resilience, cros-echelon planning, and the evolving role of AI in cyber warfare.

翻译：网络战已成为现代冲突的核心要素，在多域作战中尤其如此。作为一个独特且关键的领域，网络战需要将防御性与进攻性技术整合为连贯的战略。尽管先前的研究侧重于孤立的战术或零散的技术，但整体性理解对于有效的资源部署和风险缓解至关重要。博弈论为此提供了一个统一的框架。它不仅能够建模攻击者与防御者之间的互动，还为均衡分析、风险评估和战略推理提供了量化工具。结合现代人工智能技术，博弈论模型使得能够在网络战的多个层面——从政策与战略到作战、战术及技术实施——进行策略的设计与优化。这些模型捕捉了冲突的悖论逻辑：更多资源并不总能转化为更大优势，且非线性动态主导着结果。为阐明该方法，本章考察了合成网络冲突案例RedCyber，展示了博弈论方法如何捕捉网络作战的相互依赖性。本章最后展望了未来研究方向，包括韧性、跨梯队规划以及人工智能在网络战中不断演变的角色。