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Digital Forensics and Cyber Crime

Overview of attention for book
Cover of 'Digital Forensics and Cyber Crime'

Table of Contents

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    Book Overview
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    Chapter 1 On Efficiency and Effectiveness of Linear Function Detection Approaches for Memory Carving
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    Chapter 2 fishy - A Framework for Implementing Filesystem-Based Data Hiding Techniques
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    Chapter 3 If I Had a Million Cryptos: Cryptowallet Application Analysis and a Trojan Proof-of-Concept
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    Chapter 4 AndroParse - An Android Feature Extraction Framework and Dataset
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    Chapter 5 Digital Forensic Readiness Framework for Ransomware Investigation
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    Chapter 6 Forensics Analysis of an On-line Game over Steam Platform
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    Chapter 7 A Digital Forensic Investigation and Verification Model for Industrial Espionage
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    Chapter 8 Solid State Drive Forensics: Where Do We Stand?
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    Chapter 9 Associating Drives Based on Their Artifact and Metadata Distributions
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    Chapter 10 Digital Forensics Event Graph Reconstruction
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    Chapter 11 Multi-item Passphrases: A Self-adaptive Approach Against Offline Guessing Attacks
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    Chapter 12 Hybrid Intrusion Detection System for Worm Attacks Based on Their Network Behavior
Attention for Chapter 7: A Digital Forensic Investigation and Verification Model for Industrial Espionage
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Citations

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Readers on

mendeley
17 Mendeley
Summary Dimensions citations
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Chapter title
A Digital Forensic Investigation and Verification Model for Industrial Espionage
Chapter number 7
Book title
Digital Forensics and Cyber Crime
Published by
Springer, Cham, September 2018
DOI 10.1007/978-3-030-05487-8_7
Book ISBNs
978-3-03-005486-1, 978-3-03-005487-8
Authors

Jieun Dokko, Michael Shin

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 18%
Student > Doctoral Student 2 12%
Student > Bachelor 2 12%
Librarian 1 6%
Lecturer 1 6%
Other 3 18%
Unknown 5 29%
Readers by discipline Count As %
Computer Science 8 47%
Social Sciences 2 12%
Engineering 1 6%
Unknown 6 35%

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