Confluence of AI, Machine, and Deep Learning in Cyber Forensics
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Confluence of AI, Machine, and Deep Learning in Cyber Forensics

Sanjay Misra (Covenant University, Nigeria), Chamundeswari Arumugam (Sri Sivasubramaniya Nadar College of Engineering, India), Suresh Jaganathan (Sri Sivasubramaniya Nadar College of Engineering, India) and Saraswathi S. (Sri Sivasubramaniya Nadar College of Engineering, India)
Release Date: December, 2020|Copyright: © 2021 |Pages: 248|DOI: 10.4018/978-1-7998-4900-1
ISBN13: 9781799849001|ISBN10: 1799849007|EISBN13: 9781799849018|ISBN13 Softcover: 9781799858386
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Description

Developing a knowledge model helps to formalize the difficult task of analyzing crime incidents in addition to preserving and presenting the digital evidence for legal processing. The use of data analytics techniques to collect evidence assists forensic investigators in following the standard set of forensic procedures, techniques, and methods used for evidence collection and extraction. Varieties of data sources and information can be uniquely identified, physically isolated from the crime scene, protected, stored, and transmitted for investigation using AI techniques. With such large volumes of forensic data being processed, different deep learning techniques may be employed.

Confluence of AI, Machine, and Deep Learning in Cyber Forensics contains cutting-edge research on the latest AI techniques being used to design and build solutions that address prevailing issues in cyber forensics and that will support efficient and effective investigations. This book seeks to understand the value of the deep learning algorithm to handle evidence data as well as the usage of neural networks to analyze investigation data. Other themes that are explored include machine learning algorithms that allow machines to interact with the evidence, deep learning algorithms that can handle evidence acquisition and preservation, and techniques in both fields that allow for the analysis of huge amounts of data collected during a forensic investigation. This book is ideally intended for forensics experts, forensic investigators, cyber forensic practitioners, researchers, academicians, and students interested in cyber forensics, computer science and engineering, information technology, and electronics and communication.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Intelligence
  • Blockchain
  • Cloud Computing
  • Cyber Forensics
  • Cybercrime
  • Data Analytics
  • Deep Learning
  • Machine Learning
  • Mobile Forensics
  • Software Development

Table of Contents and List of Contributors

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