Machine Learning for Authorship Attribution and Cyber Forensics
Authors: Iqbal, Farkhund, Debbabi, Mourad, Fung, Benjamin C. M.
Free Preview- Unified approach to investigate digital crimes and identify suspects together with their collaborators and facilitators
- Customized data mining and machine learning methods for investigating cyber-attacks and online crimes
- In-depth study of methods in evidenced-based authorship analysis
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- About this book
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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.
- Table of contents (11 chapters)
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Cybersecurity And Cybercrime Investigation
Pages 1-21
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Messaging Forensics In Perspective
Pages 23-36
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Analyzing Network Level Information
Pages 37-44
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Authorship Analysis Approaches
Pages 45-56
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Writeprint Mining For Authorship Attribution
Pages 57-74
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Table of contents (11 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Machine Learning for Authorship Attribution and Cyber Forensics
- Authors
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- Farkhund Iqbal
- Mourad Debbabi
- Benjamin C. M. Fung
- Series Title
- International Series on Computer Entertainment and Media Technology
- Copyright
- 2020
- Publisher
- Springer International Publishing
- Copyright Holder
- The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
- eBook ISBN
- 978-3-030-61675-5
- DOI
- 10.1007/978-3-030-61675-5
- Hardcover ISBN
- 978-3-030-61674-8
- Series ISSN
- 2364-947X
- Edition Number
- 1
- Number of Pages
- IX, 158
- Number of Illustrations
- 10 b/w illustrations, 28 illustrations in colour
- Topics
