Detecting malicious software by monitoring anomalous windows registry accesses

  • Authors:
  • Frank Apap;Andrew Honig;Shlomo Hershkop;Eleazar Eskin;Sal Stolfo

  • Affiliations:
  • Department of Computer Science, Columbia University, New York, NY;Department of Computer Science, Columbia University, New York, NY;Department of Computer Science, Columbia University, New York, NY;Department of Computer Science, Columbia University, New York, NY;Department of Computer Science, Columbia University, New York, NY

  • Venue:
  • RAID'02 Proceedings of the 5th international conference on Recent advances in intrusion detection
  • Year:
  • 2002

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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