An Application of Machine Learning to Anomaly Detection
Terran D.R. Lane · 1999
The anomaly detection problem has been widely studied in the computer security literature. In this paper we present a machine learning approach to anomaly detection. Our system builds user profiles based on command sequences and compares current input sequences to the profile using a similarity measure. The system must learn to classify current behavior as consistent or anomalous with past behavior using only positive examples of the account's valid user. Our empirical results demonstrate that this is a promising approach to distinguishing the legitamate user from an intruder. Keywords: Computer security, Anomaly detection, Machine learning. Email: [email protected] Phone: +1 317 494-0635 Fax: +1 317 494-6440 An Application of Machine Learning to Anomaly Detection Abstract The anomaly detection problem has been widely studied in the computer security literature. In this paper we present a machine learning approach to anomaly detection. Our system builds user profiles based on...