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Home / Papers / INTRUSION DETECTION SYSTEM

INTRUSION DETECTION SYSTEM

2 Citations•2018•
Arslan G. Mustafaev
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The results of the experiments show that the approach proposed in the paper is accurate enough, with a low number of false positives and high sensitivity, requiring less training time than using a complete set of data.

Abstract

Intrusion detection systems classify network traffic into two main categories: normal activity and the actions of an attacker. Currently, intelligent data processing and machine learning play an important role in many areas of activity, not excluding intrusion detection systems. One of the main steps in data mining is the identification of an optimal data set that helps to improve the efficiency, performance and speed of predicting intrusion detection systems. For the experimental analysis, a NSL-KDD database used. The results of the experiments show that the approach proposed in the paper is accurate enough, with a low number of false positives and high sensitivity, requiring less training time than using a complete set of data.