【24h】

Efficient Parallel Muti-pattern Matching Using GPGPU Acceleration for Packet Filtering

机译:使用GPGPU加速进行数据包过滤的高效并行多模式匹配

获取原文
获取原文并翻译 | 示例

摘要

In the past decades, the Internet usage has increased dramatically. For the network security, the network packet filtering is an important strategy to identify malicious network packets. However, malicious attacks spread much faster than network administrators can respond. The software-only implementations of filter are unlikely to meet the performance goals. Therefore, we develop a novel GPGPU-based parallel packet classification approach by adopting bloom filter to inspect the packet payload by leveraging the computation power of GPGPU. The experiment results present that the proposed algorithm can be significantly enhanced the performance of filtering packets. According to the experimental results, the proposed method can achieve over 5.4 times speed up over the sequential bloom filter on single CPU.
机译:在过去的几十年中,Internet使用量急剧增加。为了网络安全,网络数据包过滤是识别恶意网络数据包的重要策略。但是,恶意攻击的传播速度远远超过网络管理员的响应速度。过滤器的纯软件实现不太可能达到性能目标。因此,我们通过利用布隆过滤器来利用GPGPU的计算能力来检查数据包有效负载,从而开发了一种基于GPGPU的并行数据包分类方法。实验结果表明,该算法可以显着提高包过滤性能。根据实验结果,所提出的方法可以比单CPU上的顺序布隆过滤器提高5.4倍以上的速度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号