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IP traceback-based intelligent packet filtering: a novel technique for defending against Internet DDoS attacks

机译:基于IP追溯的智能数据包过滤:一种防御Internet DDoS攻击的新技术

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Distributed denial of service (DDoS) is one of the most difficult security problems to address. While many existing techniques (e.g., IP traceback) focus on tracking the location of the attackers after-the-fact, little is done to mitigate the effect of an attack while it is raging on. We present a novel technique that can effectively filter out the majority of DDoS traffic, thus improving the overall throughput of the legitimate traffic. The proposed scheme leverages on and generalizes the IP traceback schemes to obtain the information concerning whether a network edge is on the attacking path of an attacker ("infected") or not ("clean"). We observe that while an attacker will have all the edges on its path marked as "infected", edges on the path of a legitimate client will mostly be "clean". By preferentially filtering out packets that are inscribed with the marks of "infected" edges, the proposed scheme removes most of the DDoS traffic while affecting legitimate traffic only slightly. Simulation results based on real-world network topologies (e.g., Skitter) all demonstrate that the proposed technique can improve the throughput of legitimate traffic by 3 to 7 times during DDoS attacks.
机译:分布式拒绝服务(DDoS)是最难解决的安全问题之一。虽然许多现有技术(例如IP追溯)集中于事后跟踪攻击者的位置,但在攻击肆虐之时却无济于事。我们提出了一种新颖的技术,可以有效过滤掉大多数DDoS流​​量,从而提高合法流量的整体吞吐量。所提出的方案利用并泛化了IP回溯方案,以获得有关网络边缘是否在攻击者(“感染”)的攻击路径上(“干净”)的信息。我们观察到,虽然攻击者将其路径上的所有边缘标记为“已感染”,但合法客户端的路径上的边缘大部分将是“干净的”。通过优先过滤掉刻有“受感染”边缘标记的数据包,所提出的方案可以删除大多数DDoS流​​量,而对合法流量的影响很小。基于现实世界网络拓扑(例如Skitter)的仿真结果均表明,该技术可以在DDoS攻击期间将合法流量的吞吐量提高3至7倍。

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