Design of Intrusion Detection Model Based on FP-Growth and Dynamic Rule Generation with Clustering

Provided by: Accent
Topic: Security
Format: PDF
Intrusion detection is the process used to identify intrusions. If the authors think of the current scenario then several new intrusion that cannot be prevented by the previous algorithm, IDS is introduced to detect possible violations of a security policy by monitoring system activities and response in all times for betterment. If they detect the attack type in a particular communication environment, a response can be initiated to prevent or minimize the damage to the system. So it is a crucial concern. In this paper, they present an efficient framework for intrusion detection which is based on Association Rule Mining (ARM) and k-means clustering.

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