A Method of Data Preprocessing for Network Security Situational Awareness Based on Conditional Random Fields
Aiping Lü, Jianping Li · 2012
Network Security Situational Awareness(NSSA) has been a hot research in the network security domain. Because of the large amount of Intrusion Detection System (IDS), We propose a new method of data preprocessing for NSSA based on conditional random fields(CRFs). It takes advantages of the CRFs models which can stitch to sequence data marking and add random attributes to deal with the amount of data from IDS, and provide the data for NSSA. It uses KDD Cup 1999 data sets as experimental data and comes to a conclusion that our proposed method is practicable, reliable and efficient.