OVERVIEW OF MACHINE LEARNING IN CYBERSECURITY COMPARATIVE ANALYSIS OF CLASSIFIERS USING WEKA

Abstract

Technologies have made a drastic change over years from mainframe computers to laptops, from telephone to cellular phone everything is changing and becoming digital. The online platform is the new way of working whether it is related to education, social gathering or business everything is going online which is easy, comfortable and consumes less time. Smart tv smartphones smartwatches that come under the category of IoT has been deployed all over the world nowadays, features like voice recognition system face detection system have become a crucial part of the most of the smart device. Nowadays it has become an essential part of our daily life but with the benefits, there is also a major concern that is increasing day by day that is cyber-attack. Security over cyberspace is a most crucial thing what user seeks for When security & machine learning both come into one picture it makes a huge impact on user’s safety. This research paper deals with the overview of machine learning and the need for machine learning in cybersecurity. I have also performed a comparison between two classifiers Naïve Bayes and decision tree by feeding the spam email dataset in the WEKA tool. The motive behind doing this classification is to check which classifier can interpret the result more accurately.