We describe and implement an approach to intrusion detection using data mining. We focus on analyzing network-based alert logs, and show how valuable information can be extracted from this data using an integrated collection of tools and technologies. These include data enhancement using topology information, event rate analysis, and temporal association. Applying these techniques on real data leads to a considerable reduction in false alarm rate while also allowing low frequency attack patterns and coordinated attacks from multiple sites to be detected.
By: Mark Mei, David A. George, Mark Brodie, Charu Aggarwal, Sheng Ma, Philip S. Yu
Published in: RC23011 in 2003
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