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Artificial Intelligence and Blockchain in Digital Forensics.

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Over the past two decades, improvements in the information technology landscape have made the collection, preservation, and analysis of digital evidence extremely important. This book can provide a wide-ranging overview of how AI and blockchain can be used to solve problems in digital forensics usin...

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Bibliographic Details
Corporate Author: Taylor & Francis
Other Authors: Kārttikēyan̲, Pa, Pande, Hari Mohan, Sarveshwaran, Velliangiri
Format: eBook
Language:English
Published: Milton : River Publishers, 2023.
Series:River Publishers Series in Digital Security and Forensics
Subjects:
Digital forensic science.
Artificial intelligence.
Blockchains (Databases)
Intelligence artificielle.
Chaînes de blocs.
artificial intelligence.
COMPUTERS / Programming / Systems Analysis & Design
LAW / Forensic Science
SCIENCE / Energy
Artificial intelligence
Digital forensic science
Electronic books.
Online Access:Connect to the full text of this electronic book
Connect to the full text of this electornic book
Table of Contents:
  • Cover
  • Half Title
  • Untitled
  • Series
  • Title
  • Copyright
  • Table of Contents
  • Preface
  • Acknowledgment
  • List of Contributors
  • List of Figures
  • List of Tables
  • List of Abbreviations
  • 1 Digital Forensics Meets AI: A Game-changer for the 4th Industrial Revolution
  • 1.1 Introduction
  • 1.2 Digital Forensics
  • 1.2.1 Growing need for digital forensics
  • 1.2.2 Process of digital forensics
  • 1.2.3 Advantages offered and limitations confronted by digital forensics
  • 1.3 AI and Digital Forensics
  • 1.3.1 Contribution of AI in the realm of digital forensics
  • 1.3.1.1 Knowledge representation
  • 1.3.1.2 Reasoning process
  • 1.3.1.3 Pattern recognition
  • 1.3.1.4 Knowledge discovery
  • 1.3.1.5 Adaptation
  • 1.3.2 Different variants of AI-based digital forensics
  • 1.3.3 AI techniques used by digital forensics investigators
  • 1.3.4 Deep learning tools and techniques helping in the domain of digital forensics
  • 1.4 Latest AI Trends Impacting Digital Forensics
  • 1.4.1 AI has taken a leap from novelty to necessity
  • 1.4.2 Data-driven AI can generate valuable content
  • 1.4.3 Smaller datasets are as amenable as big data
  • 1.4.4 Edge analytics: An upcoming AI trend
  • 1.4.5 Citizen data scientists: The next big thing under AI
  • 1.4.6 AI has an ethical and responsible role in society
  • 1.5 Challenges and the Road Ahead
  • 1.5.1 Key challenges to be addressed
  • 1.5.1.1 Heterogeneity, resulting in lack of standardization
  • 1.5.1.2 AI can be a double-edged sword
  • 1.5.1.3 Privacy-preserving and legitimacy outcry
  • 1.5.2 Road to the future
  • 1.6 Conclusion
  • References
  • 2 Mitigating and Controlling Virtual Addiction Through Web Forensics and Deep Learning
  • 2.1 Introduction
  • 2.2 Internet Addiction (IA) Types
  • 2.2.1 Cyberbullying addiction
  • 2.2.2 Web obligations
  • 2.2.3 Addiction to cyberspace relationships
  • 2.2.4 Anxious searching for content
  • 2.2.5 Gaming addiction
  • 2.2.6 Smartphone mobile app addiction
  • 2.3 Human Behavior Analysis
  • 2.4 Deep Learning's Relevance to HumanBehavior Prediction
  • 2.5 Forms of online mining
  • 2.5.1 HTML page information extraction
  • 2.5.2 Commonly associated metadata extraction
  • 2.5.3 Customized web usage monitoring
  • 2.6 Web Usage Mining Process
  • 2.7 RNN-based Analysis of Web History Log Data
  • 2.8 Feed-forward Networks Versus RNNs
  • 2.9 RNN Relying on LSTM
  • 2.10 Various Categories of Forensics
  • 2.10.1 Digital forensics
  • 2.10.2 Forensics over networking
  • 2.10.3 Web forensics
  • 2.10.4 Cloud forensics
  • 2.10.5 Mobile forensics
  • 2.10.6 Web browser forensics
  • 2.11 Web Browser Artifacts
  • 2.11.1 Navigation history
  • 2.11.2 Autocomplete data
  • 2.11.3 Cache
  • 2.11.4 Favicons
  • 2.11.5 Browser session storage
  • 2.11.6 Form data
  • 2.12 Analysis of Website Usage History
  • 2.13 Conclusion
  • 2.14 Acknowledgement
  • References