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Cyber Threat Intelligence

Overview of attention for book
Cover of 'Cyber Threat Intelligence'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Cyber Threat Intelligence: Challenges and Opportunities
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    Chapter 2 Machine Learning Aided Static Malware Analysis: A Survey and Tutorial
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    Chapter 3 Application of Machine Learning Techniques to Detecting Anomalies in Communication Networks: Datasets and Feature Selection Algorithms
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    Chapter 4 Application of Machine Learning Techniques to Detecting Anomalies in Communication Networks: Classification Algorithms
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    Chapter 5 Leveraging Machine Learning Techniques for Windows Ransomware Network Traffic Detection
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    Chapter 6 Leveraging Support Vector Machine for Opcode Density Based Detection of Crypto-Ransomware
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    Chapter 7 BoTShark: A Deep Learning Approach for Botnet Traffic Detection
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    Chapter 8 A Practical Analysis of the Rise in Mobile Phishing
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    Chapter 9 PDF-Malware Detection: A Survey and Taxonomy of Current Techniques
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    Chapter 10 Adaptive Traffic Fingerprinting for Darknet Threat Intelligence
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    Chapter 11 A Model for Android and iOS Applications Risk Calculation: CVSS Analysis and Enhancement Using Case-Control Studies
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    Chapter 12 A Honeypot Proxy Framework for Deceiving Attackers with Fabricated Content
  14. Altmetric Badge
    Chapter 13 Investigating the Possibility of Data Leakage in Time of Live VM Migration
  15. Altmetric Badge
    Chapter 14 Forensics Investigation of OpenFlow-Based SDN Platforms
  16. Altmetric Badge
    Chapter 15 Mobile Forensics: A Bibliometric Analysis
  17. Altmetric Badge
    Chapter 16 Emerging from the Cloud: A Bibliometric Analysis of Cloud Forensics Studies
Attention for Chapter 7: BoTShark: A Deep Learning Approach for Botnet Traffic Detection
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Summary Wikipedia
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Chapter title
BoTShark: A Deep Learning Approach for Botnet Traffic Detection
Chapter number 7
Book title
Cyber Threat Intelligence
Published by
Springer, Cham, January 2018
DOI 10.1007/978-3-319-73951-9_7
Book ISBNs
978-3-31-973950-2, 978-3-31-973951-9
Authors

Sajad Homayoun, Marzieh Ahmadzadeh, Sattar Hashemi, Ali Dehghantanha, Raouf Khayami, Homayoun, Sajad, Ahmadzadeh, Marzieh, Hashemi, Sattar, Dehghantanha, Ali, Khayami, Raouf

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 80 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 15%
Student > Master 10 13%
Lecturer 5 6%
Student > Bachelor 5 6%
Lecturer > Senior Lecturer 4 5%
Other 13 16%
Unknown 31 39%
Readers by discipline Count As %
Computer Science 34 43%
Engineering 6 8%
Unspecified 2 3%
Biochemistry, Genetics and Molecular Biology 2 3%
Earth and Planetary Sciences 2 3%
Other 2 3%
Unknown 32 40%

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