Zhang Xiaolu, Choo Kim-Kwang Raymond Digital Forensic Education: An Experiential Learning Approach 9783030235468

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Автор: Zhang Xiaolu, Choo Kim-Kwang Raymond
Название: Digital Forensic Education: An Experiential Learning Approach
ISBN: 9783030235468
Издательство: Springer
Классификация:

Преступность и криминология

Базы данных

Искусственный интеллект

ISBN-10: 3030235467
Обложка/Формат: Hardcover
Страницы: 307
Вес: 0.63 кг.
Дата издания: 08.08.2019
Серия: Studies in big data
Язык: English
Издание: 1st ed. 2020
Иллюстрации: 230 illustrations, color; 54 illustrations, black and white; xii, 307 p. 284 illus., 230 illus. in color.
Размер: 234 x 156 x 19
Читательская аудитория: Professional & vocational
Подзаголовок: An experiential learning approach
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: 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.
Дополнительное описание: DFRWS IoT Forensic Challenge.- Alexa and Google Home Forensics.- Digital Forensics of Raspberry Pi used for MITM.- Forensic Analysis on kindle and android.- Mobile forensics.- SSD Forensics Evidence Generation and Analysis.- Web Browser Forensics in Googl

Digital Forensic Education: An Experiential Learning Approach, Zhang Xiaolu, Choo Kim-Kwang Raymond