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Forecasting the Traits of Cyber Criminals Based on Case Studies
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Author(s): Nandini Bansod (Shri Vaishnav Institute of Forensic Science, Shri Vaishnav Vidyapeeth Vishwavidyalaya, India), Dinesh Baban Kamble (Shri Vaishnav Vidyapeeth Vishwavidyalaya, India), Rina Mishra (Shri Vaishnav Vidyapeeth Vishwavidyalaya, India)and Megha Kuliha (Shri Govindram Seksaria Institute of Technology and Science, India)
Copyright: 2022
Pages: 15
Source title:
Dark Web Pattern Recognition and Crime Analysis Using Machine Intelligence
Source Author(s)/Editor(s): Romil Rawat (Shri Vaishnav Vidyapeeth Vishwavidyalaya, India), Shrikant Telang (Shri Vaishnav Vidyapeeth Vishwavidyalaya, India), P. William (Sanjivani College of Engineering, Savitribai Phule Pune University, India), Upinder Kaur (Akal University, Talwandi Sabo, India)and Om Kumar C.U. (School of Computer Science and Engineering (SCOPE),Vellore Institute of Technology, India)
DOI: 10.4018/978-1-6684-3942-5.ch015
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Abstract
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.
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