The Integrated Bayesian Framework based on Graphics for Behavior Profiling of Anomaly Intrusion Detection

摘要

Most intrusion detection systems detect only known attack type as IDS is doing based on misuse detection, and active correspondence is difficult in new attack. In this paper, we propose an behavior profiling method using Integrated Bayesian Framework based on graphics from audit data and visualize behavior profile to detect/analyze anomaly behavior. We achieve simulation to t ranslate integrated audit data of host and network into IBF-XML which is behavior profile of semi-s tfuctured data type for anomaly detection and to visualize IBF-XML as SVG.