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Advances in Digital Forensics XIII

Overview of attention for book
Cover of 'Advances in Digital Forensics XIII'

Table of Contents

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    Book Overview
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    Chapter 1 Establishing Findings in Digital Forensic Examinations: A Case Study Method
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    Chapter 2 A Model for Digital Evidence Admissibility Assessment
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    Chapter 3 Evaluating the Authenticity of Smartphone Evidence
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    Chapter 4 Forensic Evaluation of an Amazon Fire TV Stick
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    Chapter 5 Detecting Anomalous Programmable Logic Controller Events Using Machine Learning
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    Chapter 6 A Forensic Methodology for Software-Defined Network Switches
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    Chapter 7 Identifying Evidence for Cloud Forensic Analysis
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    Chapter 8 Digital Forensic Implications of Collusion Attacks on the Lightning Network
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    Chapter 9 Insider Threat Detection Using Time-Series-Based Raw Disk Forensic Analysis
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    Chapter 10 Anti-Forensic Threat Modeling
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    Chapter 11 A Behavior-Based Approach for Malware Detection
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    Chapter 12 Categorizing Mobile Device Malware Based on System Side-Effects
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    Chapter 13 Semantic Video Carving Using Perceptual Hashing and Optical Flow
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    Chapter 14 Detecting Fraudulent Bank Checks
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    Chapter 15 Automated Collection and Correlation of File Provenance Information
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    Chapter 16 Using Personal Information in Targeted Grammar-Based Probabilistic Password Attacks
Attention for Chapter 2: A Model for Digital Evidence Admissibility Assessment
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Citations

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Chapter title
A Model for Digital Evidence Admissibility Assessment
Chapter number 2
Book title
Advances in Digital Forensics XIII
Published by
Springer, Cham, January 2017
DOI 10.1007/978-3-319-67208-3_2
Book ISBNs
978-3-31-967207-6, 978-3-31-967208-3
Authors

Albert Antwi-Boasiako, Hein Venter

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 18%
Student > Bachelor 6 11%
Lecturer 5 9%
Student > Ph. D. Student 4 7%
Student > Postgraduate 2 4%
Other 6 11%
Unknown 23 41%
Readers by discipline Count As %
Computer Science 20 36%
Engineering 4 7%
Social Sciences 3 5%
Business, Management and Accounting 1 2%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 4 7%
Unknown 23 41%

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