论文标题
具有有限理性代理的网络的安全投资：分析和分布式算法
Security Investment Over Networks with Bounded Rational Agents: Analysis and Distributed Algorithm
论文作者
论文摘要
本文考虑了通过网络上的安全投资问题，其中资源所有者的目标是将其受限的安全资源分配到战略性目标。对每个目标进行投资使其易受伤害，从而降低了其成功攻击的可能性。但是，人类倾向于认为这种概率不准确地产生有限的理性行为。在面对不确定性时，他们在决策中经常观察到的现象。我们通过累积前景理论的角度捕捉这种人性，并建立一个行为资源分配框架，以解释人类在安全投资中的误解。我们分析了这种误解行为如何通过将其与准确的感知对应物进行比较来影响资源分配计划。通过大量参与代理商，该网络可能会变得高度复杂。为此，我们进一步开发了一种完全分布的算法，以有效地计算行为安全投资策略。最后，我们证实了我们的结果，并说明了使用案例研究对资源分配方案的有限合理性的影响。
This paper considers the security investment problem over a network in which the resource owners aim to allocate their constrained security resources to heterogeneous targets strategically. Investing in each target makes it less vulnerable, and thus lowering its probability of a successful attack. However, humans tend to perceive such probabilities inaccurately yielding bounded rational behaviors; a phenomenon frequently observed in their decision-making when facing uncertainties. We capture this human nature through the lens of cumulative prospect theory and establish a behavioral resource allocation framework to account for the human's misperception in security investment. We analyze how this misperception behavior affects the resource allocation plan by comparing it with the accurate perception counterpart. The network can become highly complex with a large number of participating agents. To this end, we further develop a fully distributed algorithm to compute the behavioral security investment strategy efficiently. Finally, we corroborate our results and illustrate the impacts of human's bounded rationality on the resource allocation scheme using cases studies.
