Decision Analysis of Statistically Detecting Distributed Denial-of-Service Flooding Attacks

Ming Li (), Chi-Hung Chi (), Weijia Jia (), Wei Zhao (), Wanlei Zhou (), Jiannong Cao (), Dongyang Long () and Qiang Meng ()
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Ming Li: School of Computing, National University of Singapore, Singapore 117540, Singapore;
Chi-Hung Chi: School of Computing, National University of Singapore, Singapore 117540, Singapore
Weijia Jia: Department of Computer Engineering and Information Technology, City University of Hong Kong, Hong Kong, SAR China
Wei Zhao: Department of Computer Science, Texas A&M University, College Station, USA
Wanlei Zhou: School of Information Technology, Deakin University, Australia
Jiannong Cao: Department of Computer, Hong Kong Polytechnic University, Hong Kong, SAR China
Dongyang Long: Department of Computer Science, Zhongshan University, Guangzhou 510275, PR China
Qiang Meng: Department of Civil Engineering, National University of Singapore, Singapore 117576, Singapore

International Journal of Information Technology & Decision Making (IJITDM), 2003, vol. 02, issue 03, 397-405

Abstract: There are two statistical decision making questions regarding statistically detecting sings of denial-of-service flooding attacks. One is how to represent the distributions of detection probability, false alarm probability and miss probability. The other is how to quantitatively express a decision region within which one may make a decision that has high detection probability, low false alarm probability and low miss probability. This paper gives the answers to the above questions. In addition, a case study is demonstrated.

Keywords: Statistical decision making; statistical detection; network security; distributed denial-of-service attacks; pattern matching (search for similar items in EconPapers)
Date: 2003
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DOI: 10.1142/S0219622003000720

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