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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
  3. Altmetric Badge
    Chapter 2 Machine Learning Aided Static Malware Analysis: A Survey and Tutorial
  4. Altmetric Badge
    Chapter 3 Application of Machine Learning Techniques to Detecting Anomalies in Communication Networks: Datasets and Feature Selection Algorithms
  5. Altmetric Badge
    Chapter 4 Application of Machine Learning Techniques to Detecting Anomalies in Communication Networks: Classification Algorithms
  6. Altmetric Badge
    Chapter 5 Leveraging Machine Learning Techniques for Windows Ransomware Network Traffic Detection
  7. Altmetric Badge
    Chapter 6 Leveraging Support Vector Machine for Opcode Density Based Detection of Crypto-Ransomware
  8. Altmetric Badge
    Chapter 7 BoTShark: A Deep Learning Approach for Botnet Traffic Detection
  9. Altmetric Badge
    Chapter 8 A Practical Analysis of the Rise in Mobile Phishing
  10. Altmetric Badge
    Chapter 9 PDF-Malware Detection: A Survey and Taxonomy of Current Techniques
  11. Altmetric Badge
    Chapter 10 Adaptive Traffic Fingerprinting for Darknet Threat Intelligence
  12. Altmetric Badge
    Chapter 11 A Model for Android and iOS Applications Risk Calculation: CVSS Analysis and Enhancement Using Case-Control Studies
  13. Altmetric Badge
    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 6: Leveraging Support Vector Machine for Opcode Density Based Detection of Crypto-Ransomware
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

twitter
9 X users

Readers on

mendeley
36 Mendeley
Summary X
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Chapter title
Leveraging Support Vector Machine for Opcode Density Based Detection of Crypto-Ransomware
Chapter number 6
Book title
Cyber Threat Intelligence
Published in
arXiv, January 2018
DOI 10.1007/978-3-319-73951-9_6
Book ISBNs
978-3-31-973950-2, 978-3-31-973951-9
Authors

James Baldwin, Ali Dehghantanha, Baldwin, James, Dehghantanha, Ali

View on publisher site
X Demographics

X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 14%
Student > Master 4 11%
Lecturer 3 8%
Student > Doctoral Student 3 8%
Student > Bachelor 2 6%
Other 4 11%
Unknown 15 42%
Readers by discipline Count As %
Computer Science 15 42%
Engineering 3 8%
Psychology 1 3%
Arts and Humanities 1 3%
Unknown 16 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 August 2018.
All research outputs
#6,389,818
of 24,002,307 outputs
Outputs from arXiv
#132,328
of 1,011,770 outputs
Outputs of similar age
#123,288
of 449,341 outputs
Outputs of similar age from arXiv
#3,088
of 21,584 outputs
Altmetric has tracked 24,002,307 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 1,011,770 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 449,341 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 21,584 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.

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