Detection of DDoS Traffic by Using the Technical Analysis Used in the Stock Market

Author

Yun, Junghoon ; Chong, Song

Author_Institution

Div. of Electr. Eng., KAIST, Daejeon, South Korea

fYear

2009

Firstpage

1

Lastpage

6

Abstract

We propose a method for detecting Distributed Denial of Service (DDoS) traffic in real-time inside the network. For this purpose, we borrow the concepts of Moving Average Convergence Divergence, Rate of Change, and Relative Strength Index, which are used for technical analysis in the stock market. Due to the fact that the method is based on a quantitative, rather than a heuristic, detection level, DDoS traffic can be detected with greater accuracy (by reducing the false alarm ratio). Through detection algorithm and simulation results, we show how the detection level is determined and demonstrate the degree to which the accuracy of detection is enhanced.

Keywords

distributed processing; security of data; DDoS traffic detection; detection level; distributed denial of service; moving average convergence divergence; rate of change; relative strength index; stock market; technical analysis; Computer crime; Convergence; Detection algorithms; Entropy; Event detection; Smoothing methods; Stock markets; Telecommunication traffic; Time series analysis; Traffic control;

fLanguage

English

Publisher

ieee

Conference_Titel

Global Telecommunications Conference, 2009. GLOBECOM 2009. IEEE

Conference_Location

Honolulu, HI

ISSN

1930-529X

Print_ISBN

978-1-4244-4148-8

Type

conf

DOI

10.1109/GLOCOM.2009.5425972

Filename

5425972