论文标题
由攻击图建模的相互依赖系统的行为和游戏理论安全投资
Behavioral and Game-Theoretic Security Investments in Interdependent Systems Modeled by Attack Graphs
论文作者
论文摘要
我们考虑一个由多个相互依存资产组成的系统,以及一组捍卫者,每个人都负责确保对攻击者的一部分资产。资产之间的相互依赖性是由攻击图捕获的,其中从一个资产到另一资产的边缘表明,如果损害了以前的资产,则可以在后者的资产上发动攻击。每个边缘都有成功攻击的相关概率,捍卫者可以通过安全投资减少。在这种情况下,我们调查了在人类决策的某些特征中所产生的安全投资,这些投资已在行为经济学中确定。特别是,已经证明了人类以非线性方式感知概率,通常会超过低概率和重量不足的高概率。我们表明,在某些网络拓扑中的加权下可能会产生次优的投资。我们还表明,纯战略NASH平衡存在于具有多个(行为)捍卫者的环境中,并研究了与集中的社会最佳解决方案相比,行为捍卫者对均衡投资的效率低下。
We consider a system consisting of multiple interdependent assets, and a set of defenders, each responsible for securing a subset of the assets against an attacker. The interdependencies between the assets are captured by an attack graph, where an edge from one asset to another indicates that if the former asset is compromised, an attack can be launched on the latter asset. Each edge has an associated probability of successful attack, which can be reduced via security investments by the defenders. In such scenarios, we investigate the security investments that arise under certain features of human decision-making that have been identified in behavioral economics. In particular, humans have been shown to perceive probabilities in a nonlinear manner, typically overweighting low probabilities and underweighting high probabilities. We show that suboptimal investments can arise under such weighting in certain network topologies. We also show that pure strategy Nash equilibria exist in settings with multiple (behavioral) defenders, and study the inefficiency of the equilibrium investments by behavioral defenders compared to a centralized socially optimal solution.