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A novel feature extraction methodology using Siamese convolutional neural networks for intrusion detection

Overview of attention for article published in Cybersecurity, August 2020
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Mentioned by

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2 X users

Citations

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21 Dimensions

Readers on

mendeley
52 Mendeley
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Title
A novel feature extraction methodology using Siamese convolutional neural networks for intrusion detection
Published in
Cybersecurity, August 2020
DOI 10.1186/s42400-020-00056-4
Authors

Serafeim Moustakidis, Patrik Karlsson

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 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 9 17%
Student > Master 5 10%
Student > Ph. D. Student 4 8%
Other 2 4%
Student > Doctoral Student 1 2%
Other 1 2%
Unknown 30 58%
Readers by discipline Count As %
Computer Science 13 25%
Engineering 5 10%
Business, Management and Accounting 1 2%
Mathematics 1 2%
Social Sciences 1 2%
Other 1 2%
Unknown 30 58%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 15 August 2020.
All research outputs
#19,957,118
of 25,387,668 outputs
Outputs from Cybersecurity
#41
of 48 outputs
Outputs of similar age
#309,559
of 425,101 outputs
Outputs of similar age from Cybersecurity
#1
of 2 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 48 research outputs from this source. They receive a mean Attention Score of 4.2. This one scored the same or higher as 7 of them.
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 425,101 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them