一般Lotto博弈中的网络化多资源防御能力
Networked Multi-Resource Defense Capabilities in a General Lotto Game
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中文总结 AI 辅助
本文在一般Lotto博弈框架下，结合网络权重矩阵刻画资源对攻击的有效性，推导防御性能上下界并对比独立防御基准，为多攻击类型防御问题提供了易处理的结构。
中文摘要 AI 辅助
确保复杂系统的安全涉及战略性分配防御资源，以防止各类攻击得逞。防御者通常拥有多种防御资产，必须决定如何在不同攻击类型间最优部署其异构能力。本文将多资源分配问题建模为一般Lotto博弈，其中防御者拥有各类资源，引入的特性是资源对不同攻击类型的个体有效性由网络权重矩阵表征。分析中推导了防御者性能的上下界，并提供数值证据表明这些界是紧的；针对两种攻击类型的情况，通过解析证明界重合，建立了精确的均衡刻画。随后将本文提出的网络化多资源架构与现有文献中的独立防御基准进行数值比较，结果凸显了多攻击类型防御问题背后的基本且易处理的结构。
英文摘要
Ensuring the security of complex systems involves the strategic allocation of defensive resources to prevent various types of attacks from succeeding. A defender often has multiple types of defensive assets at its disposal, where it must decide how to optimally deploy their heterogeneous capabilities across different attack types. In this paper, we formulate a multi-resource allocation problem in the form of a General Lotto game where a defender possesses various types of resources. A feature that we introduce is that their individual effectiveness against different types of attacks is characterized by a network weight matrix. In our analysis, we derive upper and lower bounds on the performance of the defender, and provide numerical evidence suggesting that they are tight. For the case of two attack types, we analytically prove that the bounds coincide, establishing an exact equilibrium characterization. We then numerically compare our proposed networked multi-resource architecture to an independent-defense benchmark from the existing literature. These results highlight fundamental and tractable structures underlying multi-attack-type defense problems.
发表机构
- Department of Computer Science, University of Colorado Colorado Springs（科罗拉多大学斯普林斯分校计算机科学系）
机构由 AI 辅助整理，请以论文原文为准。
