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Manipulating the attacker's view of a system's attack surface

机译：操纵攻击者对系统攻击表面的看法

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Cyber attacks are typically preceded by a reconnaissance phase in which attackers aim at collecting valuable information about the target system, including network topology, service dependencies, and unpatched vulnerabilities. Unfortunately, when system configurations are static, attackers will always be able, given enough time, to acquire accurate knowledge about the target system and engineer effective exploits. To address this important problem, many adaptive techniques have been devised to dynamically change some aspects of a system's configuration in order to introduce uncertainty for the attacker. In this paper, we advance the state of the art in adaptive defense by looking at the problem from a control perspective and proposing a graph-based approach to manipulate the attacker's view of a system's attack surface. To achieve this objective, we formalize the notion of system view and distance between views. We then define a principled approach to manipulate responses to attacker's probes so as to induce an external view of the system that satisfies certain desirable properties. In particular, we propose efficient algorithmic solutions to different classes of problems, namely (i) inducing an external view that is at a minimum distance from the internal view while minimizing the cost for the defender; (ii) inducing an external view that maximizes the distance from the internal view, given an upper bound on the admissible cost for the defender. Experiments conducted on a prototypal implementation of the proposed algorithms confirm that our approach is efficient and effective in steering the attackers away from critical resources.
机译：网络攻击通常在侦察阶段之前，其中攻击者的目标是收集有关目标系统的有价值的信息，包括网络拓扑，服务依赖性和未括的漏洞。遗憾的是，当系统配置静态时，攻击者将始终能够获得足够的时间，以获得关于目标系统和工程师有效利用的准确了解。为了解决这一重要问题，已经设计了许多自适应技术来动态改变系统配置的一些方面，以便为攻击者介绍不确定性。在本文中，我们通过从控制角度来看解决问题并提出基于图形的方法来操纵攻击者的系统攻击表面的视图，推进自适应防御状态。为了实现这一目标，我们将系统视图和视图之间距离的概念正式化。然后，我们定义了一个原理的方法来操纵对攻击者的探针的响应，以便诱导满足某些所需特性的系统的外观。特别是，我们向不同类别的问题提出了高效的算法解决方案，即（i）诱导与内部视图最小的外部视图，同时最小化防御者的成本; （ii）诱导外部视图，以使距离内部视图的距离最大化，给出了对后卫的可允许费用的上限。在拟议算法的原型实施上进行的实验证实，我们的方法是有效且有效地转向远离关键资源的攻击者。

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