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Data Mining Methods for Network Intrusion Detection

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data mining - analysis

Overview Network intrusion detection systems have become a standard component in security infrastructures. Unfortunately, current systems are poor at detecting novel attacks without an unacceptable level of false alarms. This paper propose that the solution to this problem is the application of an ensemble of data mining techniques which can be applied to network connection data in an offline environment, augmenting existing real-time sensors. It expands on the motivation, particularly with regard to running in an offline environment, and the interest in multisensor and multimethod correlation. Then the paper review existing systems, from commercial systems, to research based intrusion detection systems.

Further White Paper Details
Publisher	University of California	File Format	PDF
Date Published	June 2004
Format	White Papers
Topics	Data Mining - Analysis, Security Tools, Intrusion Detection Systems

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