Adaptive Intrusion Detection Based on Boosting and Naïve Bayesian Classifier

Provided by: International Journal of Computer Applications
Topic: Security
Format: PDF
"In this paper, the authors introduce a new learning algorithm for adaptive intrusion detection using boosting and naïve Bayesian classifier, which considers a series of classifiers and combines the votes of each individual classifier for classifying an unknown or known example. The proposed algorithm generates the probability set for each round using naive Bayesian classifier and updates the weights of training examples based on the misclassification error rate that produced by the training examples in each round."

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