Machine Learning (ML) Methods to Identify Data Breaches

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Author(s): Gururaj H. L. (Vidyavardhaka College of Engineering, India), Pooja M. R. (Vidyavardhaka College of Engineering, India)and Pavan S. P. Kumar (Vidyavardhaka College of Engineering, India)
Copyright: 2022
Pages: 13
Source title: Methods, Implementation, and Application of Cyber Security Intelligence and Analytics
Source Author(s)/Editor(s): Jena Om Prakash (Ravenshaw University, India), H.L. Gururaj (Vidyavardhaka College of Engineering, India), M.R. Pooja (Vidyavardhaka College of Engineering, India)and S.P. Pavan Kumar (Vidyavardhaka College of Engineering, India)
DOI: 10.4018/978-1-6684-3991-3.ch004

Keywords: Artificial Intelligence / Computer Science & IT / Cyber and Network Security / Information Science Reference

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Abstract

In this digitized world, everything is changing from offline to online. Data plays a vital role in this digital network. The theft or loss of USB devices, computers, or mobile devices by an unauthorized person who gains access to your mobile or laptop devices, email account, or network is generally termed as a data breach. Securing data from theft and breaches is a challenging issue. It is very hard to identify data breaches in complex networks. Adding extra intelligence using machine learning (ML) approaches will be efficient in identifying such attackers. In this chapter, various ML techniques to identify data breaches such as malware attack, man in the middle (MIM), spear phishing attack, eavesdropping attack, password attack, cross-site scripting attack will be depicted with suitable case studies.

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