Improved minority attack detection in Intrusion Detection System using efficient feature selection algorithms
R. R. Rejimol Robinson,
K. P. Anagha Madhav,
Ciza Thomas
Abstract:Machine Learning and Data Mining algorithms are used extensively to enhance the performance of Intrusion Detection Systems. The number of training instances and the dimensionality of data are crucial factors affecting the performance of the model built during the training of any supervised learning algorithms. A sufficient proportion of instances having relevant features from all classes of attacks and normal traffic are considered most desirable while building the classification model that classifies the netw… Show more
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