Anomaly Detection Using Chi-square Values Based on the Typical Features and the Time Deviation

In the research of the anomaly detection system analyzing the packet header on the Internet, previous researches have proposed the anomaly detection system using chi-square values in terms of the source IP address and/or the destination port number. In these previous researches, the chi-square values were calculated from one feature causing the degradation in the False-Positive when the same symbol appears sequentially. Therefore, we propose the anomaly detection technique using chi-square values based on multi features. We also propose dynamic BIN division technique to deal with the traffic fluctuations such as day and night traffic differences. Applying our method, the chi-square values based on the time division were able to decrease the False-Positive. Our method was also able to adapt the traffic variations by applying the dynamic BIN division technique.