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Published in:
2007 | OriginalPaper | Chapter
Network-Based Anomaly Intrusion Detection Improvement by Bayesian Network and Indirect Relation
Authors : ByungRae Cha, DongSeob Lee
Published in: Knowledge-Based Intelligent Information and Engineering Systems
Publisher: Springer Berlin Heidelberg
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In this paper, Network-based anomaly intrusion detection method using Bayesian Networks was estimated probability values of behavior contexts based on Bayes theory and Indirect relation. The contexts of network-based FTP service was represented Bayesian Networks of graphic types. We profiled concisely network-based FTP behaviors using behavior context by prior, posterior and Indirect relation. And this method be able to visualize behavior profile to detect/analyze anomaly behavior. We achieve simulation to translate audit data of network into Bayesian network which is network-based behavior profile for anomaly detection.