[PDF][PDF] A K-Means and Naive Bayes learning approach for better intrusion detection
Z Muda, W Yassin, MN Sulaiman… - Information technology …, 2011 - academia.edu
Intrusion Detection Systems (TDS) have become an important building block of any sound
defense network infrastructure. Malicious attacks have brought more adverse impacts on the
networks than before, increasing the need for an effective approach to detect and identify
such attacks more effectively. In this study two learning approaches, K-Means Clustering
and Naïve Bayes classifier (KMNB) are used to perform intrusion detection. K-Means is used
to identify groups of samples that behave similarly and dissimilarly such as malicious and …
defense network infrastructure. Malicious attacks have brought more adverse impacts on the
networks than before, increasing the need for an effective approach to detect and identify
such attacks more effectively. In this study two learning approaches, K-Means Clustering
and Naïve Bayes classifier (KMNB) are used to perform intrusion detection. K-Means is used
to identify groups of samples that behave similarly and dissimilarly such as malicious and …
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