Developing custom intrusion detection filters using data mining - MILCOM 2000. 21st Century Military Communications Conference Proceedings

نویسندگان

  • Christopher Clifton
  • Chris Clifton
  • Gary Gengo
چکیده

One aspect of constructing secure networks is identifying unauthorized use of those networks. Intrusion Detection systems look for unusual or suspicious activity, such as pattems of network trafic that are likely indicators of unauthorized activity. However, normal operation often produces trafic that matches likely “attack signatures”, resulting in false alarms. We are using data mining techniques to identify sequences of alarms that likely result from normal behavior, enabling construction of filters to eliminate those alarms. This can be done at low cost for specific environments, enabling the construction of customized intrusion detection filters. We present our approach, and preliminary results identifying common sequences in alarms from a particular environment.

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تاریخ انتشار 2004