论文标题
时空移动目标防御：马尔可夫·斯塔克尔伯格游戏模型
Spatial-Temporal Moving Target Defense: A Markov Stackelberg Game Model
论文作者
论文摘要
移动目标防御已成为保护脆弱系统免受持续和隐形攻击的关键范式。为了保护系统，防御者会主动更改系统配置，以限制安全漏洞的暴露于潜在的攻击者。这样一来，辩护人为攻击者创造了不对称的不确定性和复杂性，这使他们难以妥协系统。在实践中，防御者会为系统配置的每个迁移而产生切换成本。切换成本通常取决于当前配置和以下配置。此外，不同的系统配置通常需要不同的时间来攻击者利用和攻击。因此，后卫必须同时决定系统配置的最佳序列和切换的最佳时机。在本文中，我们提出了一个马尔可夫·斯塔克伯格（Markov Stackelberg）的游戏框架，以精确地表征后卫的空间和时间决策，面对高级攻击者。我们引入了一种相对价值迭代算法，该算法计算了防御者的最佳移动目标防御策略。对现实世界问题的经验评估证明了马尔可夫·斯塔克尔伯格（Markov Stackelberg）游戏模型对时空移动目标防御的优势。
Moving target defense has emerged as a critical paradigm of protecting a vulnerable system against persistent and stealthy attacks. To protect a system, a defender proactively changes the system configurations to limit the exposure of security vulnerabilities to potential attackers. In doing so, the defender creates asymmetric uncertainty and complexity for the attackers, making it much harder for them to compromise the system. In practice, the defender incurs a switching cost for each migration of the system configurations. The switching cost usually depends on both the current configuration and the following configuration. Besides, different system configurations typically require a different amount of time for an attacker to exploit and attack. Therefore, a defender must simultaneously decide both the optimal sequences of system configurations and the optimal timing for switching. In this paper, we propose a Markov Stackelberg Game framework to precisely characterize the defender's spatial and temporal decision-making in the face of advanced attackers. We introduce a relative value iteration algorithm that computes the defender's optimal moving target defense strategies. Empirical evaluation on real-world problems demonstrates the advantages of the Markov Stackelberg game model for spatial-temporal moving target defense.
