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Optimization of FAR in Intrusion Detection System by Using Random Forest Algorithm

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Document pages: 4 pages

Abstract: Today current Network environment is very large, so security is a very vital role in networks. Internet intruders are growing, and there have been several security approaches, thusly. Assault location frameworks are utilizing different information mining methods to identify interruptions. In data security, assault discovery is essential since they endeavour to trade off the protection, unwavering quality or accessibility of an asset. One of the essential difficulties for interruption identification is the issue of misjudgement, mis-recognition and absence of continuous reaction to the assault. In this paper, experiment results are based on kddcup99 data set. Feature selection of the data set is executed using Gain Ratio (GR) and clear dissimilarity between normal and attack data is observed by using Random Forest.

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