Title :
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
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;
Conference_Titel :
Global Telecommunications Conference, 2009. GLOBECOM 2009. IEEE
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4244-4148-8
DOI :
10.1109/GLOCOM.2009.5425972
