A Game-Theoretic Framework for Securing Interdependent Assets in Networks
A Game-Theoretic Framework for Securing Interdependent Assets in Networks
复制标题
用于保护网络中相互依赖的资产的博弈论框架
DOI：
10.1007/978-3-319-75268-6_7
复制
发表时间：
2018
影响因子：
3.6
通讯作者：
S. Sundaram
中科院分区：
文献类型：
--
作者：
A. Hota;Abraham A. Clements;S. Bagchi;S. Sundaram
大型网络系统，如电网，由大量相互连接的资产组成，这些资产由多个自利益相关者管理。资产之间的相互依赖关系在整个系统的安全性中起着至关重要的作用，特别是针对利用这些相互依赖关系来攻击有价值资产的战略攻击者。在这项工作中，我们开发了一个通用的博弈论框架来模拟资源受限利益相关者针对目标攻击的安全投资。我们考虑两个互补的问题：(i)给防御者一个预算，以尽量减少由于攻击的预期损失；（ii）在防御者最大限度地减少安全投资成本的情况下，他们愿意容忍每个有价值的资产的最大安全风险。对于这两个问题，我们建立了纳什均衡的存在性，并证明了计算中央权威的最优防御分配问题和计算单个防御者的最佳响应（分散）问题可以表述为凸优化问题。然后，我们展示了我们的框架可以应用于确定网络中移动目标防御（MTD）的部署。本文首先将博弈论框架应用于ieee300总线电网，比较了集中和纳什均衡防御分配下的最优预期损失（分别是安全投资成本）。然后，我们将展示如何使用我们的框架来计算电子商务系统上MTD的最佳部署。
Large-scale networked systems, such as the power grid, are comprised of a large number of interconnected assets managed by multiple self-interested stakeholders. The interdependencies between the assets play a critical role in the security of the overall system, especially against strategic attackers who exploit these interdependencies to target valuable assets. In this work, we develop a general game-theoretic framework to model the security investments of resource-constrained stakeholders against targeted attacks. We consider two complementary problems: (i) where defenders are given a budget to minimize expected loss due to attacks and (ii) where defenders minimize security investment cost subject to a maximum security risk they are willing to tolerate per each valuable asset. For both problems, we establish the existence of Nash equilibria and show that the problem of computing the optimal defense allocation by a central authority and the (decentralized) problem of computing the best response for a single defender can be formulated as convex optimization problems. We then show that our framework can be applied to determine deployment of moving target defense (MTD) in networks. We first apply the game-theoretic framework on the IEEE 300 bus power grid network and compare the optimal expected loss (respectively, security investment cost) under centralized and Nash equilibrium defense allocations. We then show how our framework can be used to compute optimal deployment of MTD on an e-commerce system.