A new detection method for LDoS attacks based on data mining
A new detection method for LDoS attacks based on data mining
复制标题
一种基于数据挖掘的LDoS攻击检测新方法
DOI：
10.1016/j.future.2021.09.039
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发表时间：
2021-10
影响因子：
7.5
通讯作者：
Yan Yudong
中科院分区：
文献类型：
--
作者：
Tang Dan;Chen Jingwen;Wang Xiyin;Zhang Siqi;Yan Yudong
The serving capabilities of networks are reduced by low-rate denial of service (LDoS) attacks that periodically send high-intensity pulse data flows. This type of attack shows a harmful effect similar to that of traditional DoS attacks, but their attack modes differ greatly. The high concealment of LDoS attacks makes it extremely difficult for traditional DoS detection methods to detect LDoS attacks. Meanwhile, the state-of-art detection methods for LDoS attacks have low-efficiency and resource-intensive and time complexity issues. We propose a novel detection method with analysis of abnormal network traffic under LDoS attacks that combines data mining technology. The judgement benchmarks were also established. The results from the experimental simulation on the simulated environment, physical environment and public datasets prove that the developed method can effectively detect LDoS attacks with optimal detection cost and low complexity, and has a high accuracy, a low false-negative rate, and a low false-positive rate.
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