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Network intrusion detection research work that employed KDDCup 99 dataset often encounters challenges in creating classifiers that could handle unequal distributed attack categories. In such cases, classifier could not effectively learn the characteristics of rare categories, which will lead to a poor detection rate of rare categories. The efficiency of intrusion detection is mainly determined by...
This paper applies discriminative multinomial Naïve Bayes with various filtering analysis in order to build a network intrusion detection system. For our experimental analysis, we used the new NSL-KDD dataset, which is considered as a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. We perform 2 class classifications with 10-fold cross validation for building our proposed model...
With the rapid development of the Internet services and the fast increasing of intrusion problems, the traditional intrusion detection methods cannot work well with the more and more complicated intrusions. So introducing machine learning into intrusion detection systems to improve the performance has become one of the major concerns in the research of intrusion detection. Intrusion detection systems...
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