Abstract Low-rate denial of service (LDoS) attacks send attacking bursts intermittently to the network which can severely degrade the victim system’s Quality of Service (QoS). The low-rate nature of such attacks complicates attack detection. LDoS attacks repeatedly trigger the congestion control mechanism, which can make TCP traffic extremely unstable. This paper investigates the network traffic’ characteristics, in which variance and entropy are used to evaluate the TCP traffic’s characteristics, and the ratio of UDP traffic to TCP traffic (UTR) is also analyzed. Thus, a detection method combining two-step cluster analysis and UTR analysis is proposed. Through two-step cluster analysis which is one of the machine learning algorithms, network traffic is divided into multiple clusters and then clusters subjected to LDoS attacks are determined using UTR analysis. NS2 simulation platform and test-bed network environment aim to evaluate the detection approach’s performance. To better assess the effectiveness of the method, public dataset WIDE is also utilized. Experimental results with a good performance prove that the proposed detection approach can accurately detect LDoS attacks.

Dan Tang

Rui Dai

Liu Tang

Xiong Li

Human-centric Computing and Information Sciences

在以人为中心的计算和信息科学（HCIS）中，KIPS-CSWRG 发表了高质量的论文，涵盖了与以人为中心的计算和信息科学相关的各种理论和实际应用。已发表的论文展示了对解决应用服务的各种问题以及 HCIS 范围内的其他问题具有重要价值的结果。此外，我们预计它们将引发与我们未来生活相关的进一步相关研究和技术改进。

The journal "Human-centric Computing and Information Sciences" focuses on Human-centric Computing and Information Sciences (HCIS) and is published by KIPS-CSWRG. It publishes high-quality papers covering various theoretical and practical applications related to HCIS. The published papers demonstrate significant contributions to solving various issues in applied services and other important problems within the HCIS domain. Furthermore, we anticipate that these studies will inspire further research and technological advancements related to our future lives.

《Human-centric Computing and Information Sciences》期刊专注于以人为中心的计算和信息科学（HCIS），由KIPS-CSWRG出版。期刊发表高质量的论文，涵盖与以人为中心的计算和信息科学相关的各种理论和实际应用。已发表的论文展示了对解决应用服务的各种问题以及HCIS领域内其他重要问题的显著贡献。此外，我们期待这些研究能够引发与未来生活相关的进一步研究和技术改进。

Category	Quartile
计算机科学	2
计算机科学, 计算机信息系统	2

Low-rate DoS attack detection based on two-step cluster analysis and UTR analysis

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Journal Info

Category	Quartile
COMPUTER SCIENCE, INFORMATION SYSTEMS	2