Overview
- Presents an experiential learning approach to digital forensic education
- Provides an introduction to incident response and digital forensics
- Written by experts in the field
Part of the book series: Studies in Big Data (SBD, volume 61)
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Table of contents (15 chapters)
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Front Matter
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Digital Forensic Challenge Case Studeis
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Front Matter
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Technical Case Studies
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Front Matter
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Keywords
About this book
In this book, the editors explain how students enrolled in two digital forensic courses at their institution are exposed to experiential learning opportunities, where the students acquire the knowledge and skills of the subject-matter while also learning how to adapt to the ever-changing digital forensic landscape. Their findings (e.g., forensic examination of different IoT devices) are also presented in the book. Digital forensics is a topic of increasing importance as our society becomes “smarter” with more of the “things” around us been internet- and inter-connected (e.g., Internet of Things (IoT) and smart home devices); thus, the increasing likelihood that we will need to acquire data from these things in a forensically sound manner. This book is of interest to both digital forensic educators and digital forensic practitioners, as well as students seeking to learn about digital forensics.
Editors and Affiliations
Bibliographic Information
Book Title: Digital Forensic Education
Book Subtitle: An Experiential Learning Approach
Editors: Xiaolu Zhang, Kim-Kwang Raymond Choo
Series Title: Studies in Big Data
DOI: https://doi.org/10.1007/978-3-030-23547-5
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-23546-8Published: 08 August 2019
Softcover ISBN: 978-3-030-23549-9Published: 14 August 2020
eBook ISBN: 978-3-030-23547-5Published: 24 July 2019
Series ISSN: 2197-6503
Series E-ISSN: 2197-6511
Edition Number: 1
Number of Pages: XII, 307
Number of Illustrations: 54 b/w illustrations, 230 illustrations in colour
Topics: Data Engineering, Big Data, Cybercrime, Computational Intelligence, Artificial Intelligence