论文标题
网络网络的弹性反对自我传播恶意软件攻击
Cyber Network Resilience against Self-Propagating Malware Attacks
论文作者
论文摘要
近年来,自我传播恶意软件(SPM)导致了巨大的财务损失,重大数据泄露和广泛的服务中断。在本文中,我们探讨了开发能够减轻SPM攻击传播的网络弹性系统的问题。我们从对著名的自我传播恶意软件(WannaCry)的深入研究开始,并提出了一个名为Siidr的隔间模型,该模型准确地捕获了在现实世界攻击痕迹中观察到的行为。接下来,我们研究十种网络防御技术,包括现有的边缘和节点硬化策略,以及基于重新配置网络通信(Nodesplit)和隔离社区的新开发的方法。我们使用从大型零售网络收集的六个现实世界通信图详细评估了所有防御策略,并在广泛的攻击和网络拓扑中比较了它们的性能。我们表明,其中一些防御能力能够有效地减少用Siidr建模的SPM攻击的传播。例如,考虑到不使用防御的强烈攻击会感染97%的节点,从战略上获得少量节点(0.08%)会使其中一个网络中的感染足迹降低到1%。
Self-propagating malware (SPM) has led to huge financial losses, major data breaches, and widespread service disruptions in recent years. In this paper, we explore the problem of developing cyber resilient systems capable of mitigating the spread of SPM attacks. We begin with an in-depth study of a well-known self-propagating malware, WannaCry, and present a compartmental model called SIIDR that accurately captures the behavior observed in real-world attack traces. Next, we investigate ten cyber defense techniques, including existing edge and node hardening strategies, as well as newly developed methods based on reconfiguring network communication (NodeSplit) and isolating communities. We evaluate all defense strategies in detail using six real-world communication graphs collected from a large retail network and compare their performance across a wide range of attacks and network topologies. We show that several of these defenses are able to efficiently reduce the spread of SPM attacks modeled with SIIDR. For instance, given a strong attack that infects 97% of nodes when no defense is employed, strategically securing a small number of nodes (0.08%) reduces the infection footprint in one of the networks down to 1%.