A Hilbert–Huang transform approach for predicting cyber-attacks

다국어 초록 (Multilingual Abstract)

A statistical method for prediction and modeling of cyber-attack signal is proposed. The proposed method is developed by
coupling the traditional ARIMA method with Hilbert–Huang transform (HHT), designed to reduce the dimensionality and to extract
meaningful signals for reliable prediction. HHT decomposes cyber-attack signals of interest into several components including
short- and long-term patterns, and random fluctuation. Due to Hilbert transform, the method selects significant decomposed signals
that will be employed for signal prediction. Subsequently, by using the traditional dynamic models, the proposed method provides
a stable prediction of cyber-attack signal. To show the performance of the proposed method, we analyze daily worm count data
from August 1, 2005 to October 9, 2006.

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