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

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

Indexed In: SCOPUS
Release Date: December, 2020|Copyright: © 2021 |Pages: 248
DOI: 10.4018/978-1-7998-4900-1
ISBN13: 9781799849001|ISBN10: 1799849007|EISBN13: 9781799849018
Hardcover:
Available
$250.00
TOTAL SAVINGS: $250.00
Benefits
  • Printed-On-Demand (POD)
  • Usually ships one day from order
Hardcover:
Available
$250.00
TOTAL SAVINGS: $250.00
Benefits
  • Printed-On-Demand (POD)
  • Usually ships one day from order
E-Book:
Available
$250.00
TOTAL SAVINGS: $250.00
Benefits
  • Multi-user license (no added fee)
  • Immediate access after purchase
  • No DRM
  • PDF download
E-Book:
Available
$250.00
TOTAL SAVINGS: $250.00
Benefits
  • Immediate access after purchase
  • No DRM
  • PDF download
  • Receive a 10% Discount on eBooks
Hardcover +
E-Book:
Available
$300.00
TOTAL SAVINGS: $300.00
Benefits
  • Printed-On-Demand (POD)
  • Usually ships one day from order
  • Multi-user license (no added fee)
  • Immediate access after purchase
  • No DRM
  • PDF download
Hardcover +
E-Book:
Available
$300.00
TOTAL SAVINGS: $300.00
Benefits
  • Printed-On-Demand (POD)
  • Usually ships one day from order
  • Immediate access after purchase
  • No DRM
  • PDF download
OnDemand:
(Individual Chapters)
Available
$37.50
TOTAL SAVINGS: $37.50
Benefits
  • Purchase individual chapters from this book
  • Immediate PDF download after purchase or access through your personal library
Effective immediately, IGI Global has discontinued softcover book production. The softcover option is no longer available for direct purchase.
Description & Coverage
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.

Coverage:

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
Search this Book:
Reset
Editor/Author Biographies

Sanjay Misra is full Professor of Computer Engineering at Covenant University, Ota, Nigeria. He has 25 years of wide experience in academic administration and researches in various universities in Asia, Europe, and Africa. He is Ph.d. in Information and Know. Engg (Software Engineering) from the University of Alcala, Spain, and M.Tech.(Software Engineering) from Motilal Nehru National Institute of Technology, India. As per SciVal (SCOPUS- Elsevier) analysis- He is most productive researcher (no. 1-) in whole Nigeria during 2012-2017 & 2013-2018(in all subjects), in computer science no 1 in whole country and no 5 in whole continent(Africa) and also in Covenant University (600-800 ranked University by THE) since 2013. Total more than 300 articles with 200 coauthors around the world (the majority of them in Web of science-90 in JCR/SCIE Journals) in the core & application area of Software Engg (SQA, SPI, SPM), Web engg, Health Informatics, Intelligent systems etc. He has delivered more than 80 keynote speeches/invited talks/public lectures in reputed conferences and institutes around the world (traveled around 60 countries). He got several awards for outstanding publications (2014 IET Software Premium Award(UK)), and from TUBITAK-Turkish Higher Education, and Atilim University). He edited (with colleagues) 42 LNCS & 6 IEEE proceedings, editor in chief of book series IT Personnel and Project Management, International Journal of Human Capital and Information Technology Professionals(IJHCITP)-IGI Global, and of 3 journals(IJ) and editor in various SCIE journals.

|Chamundeswari Arumugam - Contributing Author| is a Professor of Computer Science and Engineering department at Sri Sivasubramaniya Nadar College of Engineering, Chennai, India.

Suresh Jaganathan, Associate Professor in the Department of Computer Science and Engineering, Sri Sivasubramaniya Nadar College of Engineering, has more than 22 years of teaching experience. He received his PhD in Computer Science from Jawaharlal Nehru Technological University, Hyderabad, M.E Software Engineering from Anna University and B.E Computer Science & Engineering, from Madurai Kamarajar University, Madurai. He has more than 30 publications in refereed International Journals and Conferences. Apart from this, to his credit, he has filed two patents and written a book on “Cloud Computing: A Practical Approach for Learning and Implementation”, published by Pearson Publications. He is an active reviewer in reputed journals (Elsevier - Journal of Networks and Computer Applications, Computer in Biology and Medicine). His areas of interest are Distributed Computing, Deep Learning, Data Analytics, Machine learning & Blockchain Technology.

Saraswathi S., Associate Professor in the Department of Computer Science and Engineering has around 16 years of teaching experience. She received her Ph.D. from Anna University in 2015, Masters in Computer Science & Engineering (M.E.) from Manonmaniam Sundaranar University in 2005 and Bachelor in Computer Science & Engineering (B.E.) from National Engineering College, Manonmaniam Sundaranar University in 1999. She is a member of ACM and IEEE. She has two faculty internal funded projects funded by SSN trust. Her area of research includes Network Security, Cryptography, Cyber Forensic and IOT.

Abstracting & Indexing
Archiving
All of IGI Global's content is archived via the CLOCKSS and LOCKSS initiative. Additionally, all IGI Global published content is available in IGI Global's InfoSci® platform.