论文标题
最小化对抗巡逻的预期入侵检测时间
Minimizing Expected Intrusion Detection Time in Adversarial Patrolling
论文作者
论文摘要
在对抗性巡逻游戏中，移动防御者致力于发现攻击者发起的脆弱目标的入侵。传统上，攻击者的效用是完成攻击的可能性，可能是由于目标成本加权。但是，在许多现实世界中，攻击者造成的实际损害取决于\ emph {time}自攻击启动以来所经过的\ emph {time}。我们为这种情况介绍了一个正式的模型，并表明辩护人始终具有实现最大保护的\ emph {optimal}策略。我们还证明，\ emph {有限摄像机}防守者的策略足以实现任意接近最佳的保护。然后，我们根据可区分的编程和梯度下降设计有效的\ emph {策略合成}算法。
In adversarial patrolling games, a mobile Defender strives to discover intrusions at vulnerable targets initiated by an Attacker. The Attacker's utility is traditionally defined as the probability of completing an attack, possibly weighted by target costs. However, in many real-world scenarios, the actual damage caused by the Attacker depends on the \emph{time} elapsed since the attack's initiation to its detection. We introduce a formal model for such scenarios, and we show that the Defender always has an \emph{optimal} strategy achieving maximal protection. We also prove that \emph{finite-memory} Defender's strategies are sufficient for achieving protection arbitrarily close to the optimum. Then, we design an efficient \emph{strategy synthesis} algorithm based on differentiable programming and gradient descent.
