Network Intrusion Detection System Using Naïve Bayes Classification Technique for Anomaly Detection

Abstract

This chapter focuses on the use of anomaly detection systems through Data Mining techniques. Symantec Corporation, in a recent report, uncovered that the number of phishing attacks targeted at stealing confidential information such as credit card numbers, passwords, and other financial information are on the rise, going from 70 million attacks in June 2018 to over 150 million in less than a year. The features for each link are built from the captured network traffic by the pre-processors. Naive Bayes Classification algorithm is a probabilistic classifier/class of algorithms that bases probability models that incorporate assumptions and probabilities. A Bayes classifier considers each of the above attributes to assume that the shoe is, in fact, wearable independently regardless of the correlations between condition, lace, sole, and size features. In Bayesian classification, a screening of the dataset is required, and if there are new elements introduced, then another screening is required.