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

Author

Listed:
  • Ming Li

    (School of Computing, National University of Singapore, Singapore 117540, Singapore;
    School of Information Technology, Southern Yangtze University, Wuxi 214036, PR China)

  • 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)

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.

Suggested Citation

  • Ming Li & Chi-Hung Chi & Weijia Jia & Wei Zhao & Wanlei Zhou & Jiannong Cao & Dongyang Long & Qiang Meng, 2003. "Decision Analysis of Statistically Detecting Distributed Denial-of-Service Flooding Attacks," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 397-405.
  • Handle: RePEc:wsi:ijitdm:v:02:y:2003:i:03:n:s0219622003000720
    DOI: 10.1142/S0219622003000720
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