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Advances in Digital Forensics XII

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

Table of Contents

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    Book Overview
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    Chapter 1 On a Scientific Theory of Digital Forensics
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    Chapter 2 Data Privacy Perceptions About Digital Forensic Investigations in India
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    Chapter 3 A Framework for Assessing the Core Capabilities of a Digital Forensic Organization
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    Chapter 4 Optimizing Short Message Text Sentiment Analysis for Mobile Device Forensics
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    Chapter 5 Impact of User Data Privacy Management Controls on Mobile Device Investigations
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    Chapter 6 Analyzing Mobile Device Ads to Identify Users
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    Chapter 7 A Forensic Methodology for Analyzing Nintendo 3DS Devices
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    Chapter 8 Reconstructing Interactions with Rich Internet Applications from HTTP Traces
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    Chapter 9 Reconstructing Tabbed Browser Sessions Using Metadata Associations
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    Chapter 10 A Probabilistic Network Forensic Model for Evidence Analysis
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    Chapter 11 API-Based Forensic Acquisition of Cloud Drives
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    Chapter 12 The Cloud Storage Ecosystem – A New Business Model for Internet Piracy?
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    Chapter 13 Windows 8.x Facebook and Twitter Metro App Artifacts
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    Chapter 14 Profiling Flash Mob Organizers in Web Discussion Forums
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    Chapter 15 Enhancing Image Forgery Detection Using 2-D Cross Products
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    Chapter 16 Forensic Authentication of Bank Checks
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    Chapter 17 Data Type Classification: Hierarchical Class-to-Type Modeling
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    Chapter 18 Secure File Deletion for Solid State Drives
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    Chapter 19 A Tool for Volatile Memory Acquisition from Android Devices
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    Chapter 20 Advanced Automated Disk Investigation Toolkit
Attention for Chapter 6: Analyzing Mobile Device Ads to Identify Users
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Citations

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18 Mendeley
Summary Dimensions citations
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Chapter title
Analyzing Mobile Device Ads to Identify Users
Chapter number 6
Book title
Advances in Digital Forensics XII
Published by
Springer, Cham, January 2016
DOI 10.1007/978-3-319-46279-0_6
Book ISBNs
978-3-31-946278-3, 978-3-31-946279-0
Authors

Jayaprakash Govindaraj, Robin Verma, Gaurav Gupta

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 28%
Other 1 6%
Student > Doctoral Student 1 6%
Student > Master 1 6%
Researcher 1 6%
Other 2 11%
Unknown 7 39%
Readers by discipline Count As %
Computer Science 6 33%
Economics, Econometrics and Finance 2 11%
Business, Management and Accounting 1 6%
Engineering 1 6%
Unknown 8 44%

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