Extended abstract: Anti-DDoS technique using self-learning bloom filter

C. Y. Tseung, Kam-pui Chow, X. Zhang
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引用次数: 13

Abstract

DDoS attack is still one of the major threats from Internet. We propose a new technique to mitigate different types of DDoS, combining and taking advantages of both machine learning algorithms and Bloom filter. We use machine learning to extract features of attacks, then use a customized Bloom filter to defend attacks based on selected features. We implemented and tested the performance of the proposed technique in a lab environment.
扩展摘要:基于自学习布隆滤波器的ddos防御技术
DDoS攻击仍然是来自互联网的主要威胁之一。我们提出了一种新的技术来缓解不同类型的DDoS,结合并利用机器学习算法和布隆过滤器的优势。我们使用机器学习来提取攻击的特征,然后根据选择的特征使用自定义的Bloom过滤器来防御攻击。我们在实验室环境中实现并测试了所提出技术的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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