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Detection of Intrusions and Malware, and Vulnerability Assessment

Overview of attention for book
Attention for Chapter 11: Phoenix: DGA-Based Botnet Tracking and Intelligence
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
3 tweeters

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
97 Mendeley
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Chapter title
Phoenix: DGA-Based Botnet Tracking and Intelligence
Chapter number 11
Book title
Detection of Intrusions and Malware, and Vulnerability Assessment
Published in
Lecture notes in computer science, July 2014
DOI 10.1007/978-3-319-08509-8_11
Book ISBNs
978-3-31-908508-1, 978-3-31-908509-8
Authors

Stefano Schiavoni, Federico Maggi, Lorenzo Cavallaro, Stefano Zanero

Twitter Demographics

The data shown below were collected from the profiles of 3 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 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 1%
Czechia 1 1%
Unknown 95 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 31%
Researcher 14 14%
Student > Master 13 13%
Student > Bachelor 6 6%
Other 4 4%
Other 8 8%
Unknown 22 23%
Readers by discipline Count As %
Computer Science 58 60%
Engineering 6 6%
Arts and Humanities 1 1%
Unspecified 1 1%
Economics, Econometrics and Finance 1 1%
Other 3 3%
Unknown 27 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 22 September 2017.
All research outputs
#9,994,810
of 16,849,755 outputs
Outputs from Lecture notes in computer science
#3,978
of 7,735 outputs
Outputs of similar age
#91,324
of 192,924 outputs
Outputs of similar age from Lecture notes in computer science
#59
of 163 outputs
Altmetric has tracked 16,849,755 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,735 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
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 192,924 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 50% of its contemporaries.
We're also able to compare this research output to 163 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 63% of its contemporaries.