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Detection of Intrusions and Malware, and Vulnerability Assessment

Overview of attention for book
Cover of 'Detection of Intrusions and Malware, and Vulnerability Assessment'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Subverting Operating System Properties Through Evolutionary DKOM Attacks
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    Chapter 2 DeepFuzz: Triggering Vulnerabilities Deeply Hidden in Binaries
  4. Altmetric Badge
    Chapter 3 AutoRand: Automatic Keyword Randomization to Prevent Injection Attacks
  5. Altmetric Badge
    Chapter 4 AVRAND: A Software-Based Defense Against Code Reuse Attacks for AVR Embedded Devices
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    Chapter 5 Towards Vulnerability Discovery Using Staged Program Analysis
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    Chapter 6 Comprehensive Analysis and Detection of Flash-Based Malware
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    Chapter 7 Reviewer Integration and Performance Measurement for Malware Detection
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    Chapter 8 On the Lack of Consensus in Anti-Virus Decisions: Metrics and Insights on Building Ground Truths of Android Malware
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    Chapter 9 Probfuscation: An Obfuscation Approach Using Probabilistic Control Flows
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    Chapter 10 RAMBO: Run-Time Packer Analysis with Multiple Branch Observation
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    Chapter 11 Detecting Hardware-Assisted Virtualization
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    Chapter 12 Financial Lower Bounds of Online Advertising Abuse
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    Chapter 13 Google Dorks: Analysis, Creation, and New Defenses
  15. Altmetric Badge
    Chapter 14 Flush+Flush: A Fast and Stealthy Cache Attack
  16. Altmetric Badge
    Chapter 15 Rowhammer.js: A Remote Software-Induced Fault Attack in JavaScript
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    Chapter 16 Detile: Fine-Grained Information Leak Detection in Script Engines
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    Chapter 17 Understanding the Privacy Implications of ECS
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    Chapter 18 Analysing the Security of Google’s Implementation of OpenID Connect
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    Chapter 19 Leveraging Sensor Fingerprinting for Mobile Device Authentication
  21. Altmetric Badge
    Chapter 20 MtNet: A Multi-Task Neural Network for Dynamic Malware Classification
  22. Altmetric Badge
    Chapter 21 Adaptive Semantics-Aware Malware Classification
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

twitter
2 X users
patent
1 patent
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
18 Mendeley
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Title
Detection of Intrusions and Malware, and Vulnerability Assessment
Published by
Lecture notes in computer science, January 2016
DOI 10.1007/978-3-319-40667-1
ISBNs
978-3-31-940666-4, 978-3-31-940667-1
Editors

Juan Caballero, Urko Zurutuza, Ricardo J. Rodríguez

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 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 6 33%
Student > Master 3 17%
Lecturer 1 6%
Professor > Associate Professor 1 6%
Unknown 7 39%
Readers by discipline Count As %
Computer Science 9 50%
Engineering 1 6%
Unknown 8 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 02 January 2024.
All research outputs
#4,760,220
of 25,139,853 outputs
Outputs from Lecture notes in computer science
#1,030
of 8,154 outputs
Outputs of similar age
#75,049
of 405,647 outputs
Outputs of similar age from Lecture notes in computer science
#151
of 581 outputs
Altmetric has tracked 25,139,853 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,154 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done well, scoring higher than 81% 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 405,647 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 581 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.