Forecasting the Traits of Cyber Criminals Based on Case Studies
Nandini Bansod, Dinesh Baban Kamble, Rina Mishra, Megha Kuliha · Advances in digital crime, forensics, and cyber terrorism book series · 2022
The COVID-19 virus has affected every country on the globe; India is amongst the most with over 3.39 billion people who have been infected, and computer use has expanded since. As cybercrime (breaching, spoofing, DDOS assault, and phishing) is one of the most serious problems facing society today, it's crucial to understand what causes such attacks. Although many methods have been proposed to detect cybercrime, criminological theory of crime is one of them. But the most successful method for detecting these malicious activities is machine learning. This is because most of the cyberattacks have some common characteristics which can be identified by machine learning methods. In this context, an approach has been made in the chapter to review machine learning methods to understand the traits of cyber-criminals and crime committed on the dark web along with suitable methods to tackle them.