Evaluation of the Attack Effect Based on Improved Grey Clustering Model

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Author(s): Chen Yue (School of Information Technology and Network Security, People's Public Security University of China, Beijing, China), Lu Tianliang (Collaborative Innovation Center of Security and Law for Cyberspace, People's Public Security University of China, Beijing, China), Cai Manchun (Collaborative Innovation Center of Security and Law for Cyberspace, People's Public Security University of China, Beijing, China)and Li Jingying (School of Information Technology and Network Security, People's Public Security University of China, Beijing, China)
Copyright: 2021
Pages: 9
Source title: Research Anthology on Combating Denial-of-Service Attacks
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-5348-0.ch016

Keywords: Cyber and Network Security / Cyber Warfare & Terrorism / Information Science Reference / Security & Forensics

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Abstract

There are a lot of uncertainties and incomplete information problems on network attack. It is of great value to access the effect of the attack in the current network attack and defense. This paper examines the characteristics of network attacks, there are problems with traditional clustering that index attribution is not clear and the cross of clustering interval. A two-stage grey synthetic clustering evaluation model based on center-point triangular whitenization weight function was proposed for the attack effect. The authors studied the feasibility of applying this model to the evaluation of network attack effect. Finally, an example is given, which showed the model could evaluate the effect of the denial-of-service attack precisely. It is also shown that the model is viable to evaluate the attack effect.

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Evaluation of the Attack Effect Based on Improved Grey Clustering Model

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