Machine Learning for Authorship Attribution and Cyber Forensics

Machine Learning for Authorship Attribution and Cyber Forensics
Author :
Publisher : Springer Nature
Total Pages : 158
Release :
ISBN-10 : 9783030616755
ISBN-13 : 3030616754
Rating : 4/5 (55 Downloads)

Book Synopsis Machine Learning for Authorship Attribution and Cyber Forensics by : Farkhund Iqbal

Download or read book Machine Learning for Authorship Attribution and Cyber Forensics written by Farkhund Iqbal and published by Springer Nature. This book was released on 2020-12-04 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book first explores the cybersecurity’s landscape and the inherent susceptibility of online communication system such as e-mail, chat conversation and social media in cybercrimes. Common sources and resources of digital crimes, their causes and effects together with the emerging threats for society are illustrated in this book. This book not only explores the growing needs of cybersecurity and digital forensics but also investigates relevant technologies and methods to meet the said needs. Knowledge discovery, machine learning and data analytics are explored for collecting cyber-intelligence and forensics evidence on cybercrimes. Online communication documents, which are the main source of cybercrimes are investigated from two perspectives: the crime and the criminal. AI and machine learning methods are applied to detect illegal and criminal activities such as bot distribution, drug trafficking and child pornography. Authorship analysis is applied to identify the potential suspects and their social linguistics characteristics. Deep learning together with frequent pattern mining and link mining techniques are applied to trace the potential collaborators of the identified criminals. Finally, the aim of the book is not only to investigate the crimes and identify the potential suspects but, as well, to collect solid and precise forensics evidence to prosecute the suspects in the court of law.


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