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Handbook of Big Data and IoT Security

Overview of attention for book
Cover of 'Handbook of Big Data and IoT Security'

Table of Contents

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    Book Overview
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    Chapter 1 Big Data and Internet of Things Security and Forensics: Challenges and Opportunities
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    Chapter 2 Privacy of Big Data: A Review
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    Chapter 3 A Bibliometric Analysis of Authentication and Access Control in IoT Devices
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    Chapter 4 Towards Indeterminacy-Tolerant Access Control in IoT
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    Chapter 5 Private Cloud Storage Forensics: Seafile as a Case Study
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    Chapter 6 Distributed Filesystem Forensics: Ceph as a Case Study
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    Chapter 7 Forensic Investigation of Cross Platform Massively Multiplayer Online Games: Minecraft as a Case Study
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    Chapter 8 Big Data Forensics: Hadoop Distributed File Systems as a Case Study
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    Chapter 9 Internet of Things Camera Identification Algorithm Based on Sensor Pattern Noise Using Color Filter Array and Wavelet Transform
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    Chapter 10 Protecting IoT and ICS Platforms Against Advanced Persistent Threat Actors: Analysis of APT1, Silent Chollima and Molerats
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    Chapter 11 Analysis of APT Actors Targeting IoT and Big Data Systems: Shell_Crew, NetTraveler, ProjectSauron, CopyKittens, Volatile Cedar and Transparent Tribe as a Case Study
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    Chapter 12 A Cyber Kill Chain Based Analysis of Remote Access Trojans
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    Chapter 13 Evaluation and Application of Two Fuzzing Approaches for Security Testing of IoT Applications
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    Chapter 14 Bibliometric Analysis on the Rise of Cloud Security
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    Chapter 15 A Bibliometric Analysis of Botnet Detection Techniques
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    Chapter 16 Security in Online Games: Current Implementations and Challenges
Overall attention for this book and its chapters
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54 Mendeley
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Handbook of Big Data and IoT Security
Published by
Springer International Publishing, July 2019
DOI 10.1007/978-3-030-10543-3
978-3-03-010542-6, 978-3-03-010543-3

Dehghantanha, Ali, Choo, Kim-Kwang Raymond

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 28%
Student > Master 8 15%
Student > Bachelor 6 11%
Researcher 6 11%
Lecturer 5 9%
Other 4 7%
Unknown 10 19%
Readers by discipline Count As %
Computer Science 29 54%
Engineering 7 13%
Business, Management and Accounting 3 6%
Social Sciences 1 2%
Medicine and Dentistry 1 2%
Other 2 4%
Unknown 11 20%