论文标题

防御具有资源重新分配网络上传染性攻击

Defending against Contagious Attacks on a Network with Resource Reallocation

论文作者

Bai, Rufan, Lin, Haoxing, Yang, Xinyu, Wu, Xiaowei, Li, Minming, Jia, Weijia

论文摘要

在经典的网络安全游戏中,防御者将防御资源分配给网络节点,而攻击者攻击节点,目的是最大程度地造成损害。现有模型假定节点U处的攻击仅在U处造成损害。但是,在许多现实世界中的安全方案中,节点U的攻击蔓延到U的邻居,并可能在多个节点上造成损害,例如,以爆发病毒。在本文中,我们考虑了针对传染性攻击的网络捍卫问题。 研究资源共享资源的现有作品假定分配给节点的资源可以在相邻节点之间共享或重复。但是,在现实世界中,共享资源自然会导致源节点的防御能力降低,尤其是在防御传染性攻击时。为此,我们研究了分配给节点的资源只能将其转移到其相邻节点的模型,我们将其称为重新分配过程。 我们表明,在两个方面很难进行这种更通用的模型:(1)即使对于固定的资源分配,我们也表明计算最佳重新定位是NP-HARD; (2)对于不允许重新分配的情况,我们表明计算最佳分配(针对传染性攻击)也是NP-HARD。为了取得积极的结果,我们为问题提供了混合整数线性程序公式和双标准近似算法。我们的实验结果表明,我们算法的分配和重新分配策略在最大程度地降低了由于传染性攻击而造成的损害方面表现良好。

In classic network security games, the defender distributes defending resources to the nodes of the network, and the attacker attacks a node, with the objective to maximize the damage caused. Existing models assume that the attack at node u causes damage only at u. However, in many real-world security scenarios, the attack at a node u spreads to the neighbors of u and can cause damage at multiple nodes, e.g., for the outbreak of a virus. In this paper, we consider the network defending problem against contagious attacks. Existing works that study shared resources assume that the resource allocated to a node can be shared or duplicated between neighboring nodes. However, in real world, sharing resource naturally leads to a decrease in defending power of the source node, especially when defending against contagious attacks. To this end, we study the model in which resources allocated to a node can only be transferred to its neighboring nodes, which we refer to as a reallocation process. We show that this more general model is difficult in two aspects: (1) even for a fixed allocation of resources, we show that computing the optimal reallocation is NP-hard; (2) for the case when reallocation is not allowed, we show that computing the optimal allocation (against contagious attack) is also NP-hard. For positive results, we give a mixed integer linear program formulation for the problem and a bi-criteria approximation algorithm. Our experimental results demonstrate that the allocation and reallocation strategies our algorithm computes perform well in terms of minimizing the damage due to contagious attacks.

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