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Detecting Malicious Software by Monitoring Anomalous Windows Registry Accesses

Frank ApapContact Information, Andrew HonigContact Information, Shlomo HershkopContact Information, Eleazar EskinContact Information and Sal StolfoContact Information

(7)  Department of Computer Science, Columbia University, New York, NY 10027, USA
Abstract
We present a host-based intrusion detection system (IDS) for Microsoft Windows. The core of the system is an algorithm that detects attacks on a host machine by looking for anomalous accesses to the Windows Registry. The key idea is to first train a model of normal registry behavior on a windows host, and use this model to detect abnormal registry accesses at run-time. The normal model is trained using clean (attack-free) data. At run-time the model is used to check each access to the registry in real time to determine whether or not the behavior is abnormal and (possibly) corresponds to an attack. The system is effective in detecting the actions of malicious software while maintaining a low rate of false alarms

Contact Information Frank Apap
Email: fapap@cs.columbia.edu

Contact Information Andrew Honig
Email: arh@cs.columbia.edu

Contact Information Shlomo Hershkop
Email: shlomo@cs.columbia.edu

Contact Information Eleazar Eskin
Email: eeskin@cs.columbia.edu

Contact Information Sal Stolfo
Email: sal@cs.columbia.edu
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Referenced by
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  1. Ye, N. (2004) EWMA Forecast of Normal System Activity for Computer Intrusion Detection. IEEE Transactions on Reliability 53(4)
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