Security across network has become a major concern during this Covid-19 scenario. Security threats happens due to variety of reasons like theft of analytical property, software attacks, identity theft, stealing of equipment or information, sabotage, and information extraction. The wrong use of protocols over network also causes security threat. Introduction of data mining techniques in network security field plays a major role with data extraction, data transformation and analysation of the huge amount of data. The various data mining algorithms provides an insight to analyse and predict the data and the threats over the computer networks. This paper focusses on the approaches to predict security threats over networks using various classification algorithms. The four-classification algorithm majorly focussed here is Naïve Bayes Classifier, Decision Tree Classifier, K Nearest Neighbours and Logistic Regression. It compares the performance of the above-mentioned classification algorithms to detect the threats. © 2021 IEEE.
Prediction of Data Breaches using Classification Algorithms