arXiv:2603.03526cs.MAcs.AI2026-03被引 2

用多智能体影响图统一分析反混合威胁措施效果

Multi-Agent Influence Diagrams to Hybrid Threat Modeling

  • 构建多智能体影响图框架,整合不同威胁建模方法
  • 1000次仿真显示五类反制措施中威慑最有效
  • 适合政策制定者与安全战略研究者参考

西方政府已采取多种反混合威胁措施以应对低于传统军事阈值的敌对行为。然而,这些措施的实际效果因混合威胁的模糊性、跨域特性以及反制手段如何影响对手行为的不确定性而难以评估。本文提出一种新方法,通过多智能体影响图框架统一此前分裂的混合威胁建模方式,平衡反制措施的成本、威慑力及减损能力。我们基于真实场景设计了1000个半合成变体,模拟攻击方A与防御方B在关键基础设施网络攻击中的战略互动,评估五类反混合威胁措施的有效性。措施涵盖增强韧性、阻断攻击能力及惩罚威慑等策略。分析聚焦于反制措施的整体特征与参数敏感性,探讨政策意义并指出未来研究方向。

原文摘要 · Abstract (English)

Western governments have adopted an assortment of counter-hybrid threat measures to defend against hostile actions below the conventional military threshold. The impact of these measures is unclear because of the ambiguity of hybrid threats, their cross-domain nature, and uncertainty about how countermeasures shape adversarial behavior. This paper offers a novel approach to clarifying this impact by unifying previously bifurcating hybrid threat modeling methods through a (multi-agent) influence diagram framework. The model balances the costs of countermeasures, their ability to dissuade the adversary from executing hybrid threats, and their potential to mitigate the impact of hybrid threats. We run 1000 semi-synthetic variants of a real-world-inspired scenario simulating the strategic interaction between attacking agent A and defending agent B over a cyber attack on critical infrastructure to explore the effectiveness of a set of five different counter-hybrid threat measures. Counter-hybrid measures range from strengthening resilience and denial of the adversary's ability to execute a hybrid threat to dissuasion through the threat of punishment. Our analysis primarily evaluates the overarching characteristics of counter-hybrid threat measures. This approach allows us to generalize the effectiveness of these measures and examine parameter impact sensitivity. In addition, we discuss policy relevance and outline future research avenues.

威胁建模多智能体网络安全政策分析

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