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On Multi-Point, In-Network Filtering of Distributed Denial-of-Service Traffic

机译:关于分布式拒绝服务流量的多点网络内过滤

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Research has shown that distributed denial-of-service (DDoS) attacks on the Internet could often be better handled by enlisting the in-network defense of multiple autonomous systems (ASes), rather than relying entirely on the victim's Internet Service Provider at the edge. Less noticed but important is the fact that an in-network defense can also remove DDoS traffic from the Internet early en route to the victim, thus decreasing the overall load on the Internet and reducing chances of link congestion. However, it is not well understood to what degree different in-network defense strategies can achieve such benefits. In this paper, we model the existing two main categories of in-network DDoS defense algorithms (PushBack, SourceEnd) and propose a new type of algorithm (StrategicPoints). In particular, we compare their effectiveness in minimizing the amount of DDoS traffic that the victim receives, their impact on reducing the DDoS traffic on the entire Internet, and their resiliency against intelligent adversaries and dynamic attacks. We detail how the comparison results vary according to parameters and provide our insights on the pros and cons of these three categories of in-network DDoS defense solutions.
机译:研究表明,通过采用多个自治系统(ASes)的网络内防御,而不是完全依赖边缘受害者的Internet服务提供商,通常可以更好地处理Internet上的分布式拒绝服务(DDoS)攻击。 。鲜为人知但很重要的事实是,网络内防御还可以从Internet到受害者的早期删除DDoS流​​量,从而减少Internet的总体负载并减少链路拥塞的机会。但是,人们尚不了解不同的网络内防御策略可以在多大程度上实现这种优势。在本文中,我们对现有的两个主要类别的网络内DDoS防御算法(PushBack,SourceEnd)进行建模,并提出一种新型的算法(StrategicPoints)。特别是,我们比较了它们在最大程度地减少受害者接收的DDoS流​​量,减少整个Internet上的DDoS流​​量的影响以及对智能对手和动态攻击的弹性方面的有效性。我们将详细介绍比较结果如何根据参数变化,并提供我们对这三类网络内DDoS防御解决方案的优缺点的见解。

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