基于图形处理单元的下一代DDoS防御系统

Selcuk Keskin, Hasan Tugrul Erdogan, T. Koçak
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引用次数: 3

摘要

包过滤是防护系统的重要组成部分,用于保护设备所在的网络系统不受攻击。该算法通过一定的规则后,允许报文进入网络。带有决策的数据包被写入由基本网络信息组成的连接表中。在本文中,我们设计并实现了一种可用于网络连接跟踪的图形处理单元(GPU)大规模并行计算方法。结果表明,基于GPU的连接表跟踪算法达到了90,000,000数据包/秒(pps)的吞吐量,比Linux内核中定义的包过滤功能快35倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Graphics processing unit based next generation DDoS prevention system
Packet filtering is the main component of prevention systems to protect the network system of the devices against attacks. The algorithm allows the packets to access to network after passing some rules. The packets with decisions are written into a connection table that consists of essential network information. In this paper, we design and implement a massively parallel computation approach of Graphics Processing Unit (GPU) that can be used for network connection tracking. The results show that the GPU based connection table tracking algorithms achieve 90,000,000 packets per second (pps) throughput which is 35 times faster than the packet filtering function defined in Linux kernel.
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