计算机科学
服务拒绝攻击
素描
特征(语言学)
实时计算
人工智能
数据挖掘
算法
互联网
语言学
万维网
哲学
作者
Haibin Shi,Guang Cheng,Ying Hu,Fuzhou Wang,Haoxuan Ding
摘要
With the great changes in network scale and network topology, the difficulty of DDoS attack detection increases significantly. Most of the methods proposed in the past rarely considered the real-time, adaptive ability, and other practical issues in the real-world network attack detection environment. In this paper, we proposed a real-time adaptive DDoS attack detection method RT-SAD, based on the response to the external network when attacked. We designed a feature extraction method based on sketch and an adaptive updating algorithm, which makes the method suitable for the high-speed network environment. Experiment results show that our method can detect DDoS attacks using sampled Netflowunder high-speed network environment, with good real-time performance, low resource consumption, and high detection accuracy.
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