| Title |
Applications of machine learning techniques in side-channel attacks: a survey
|
|---|---|
| Published in |
Journal of Cryptographic Engineering, April 2019
|
| DOI | 10.1007/s13389-019-00212-8 |
| Authors |
Benjamin Hettwer, Stefan Gehrer, Tim Güneysu |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 25% |
| Nigeria | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Science communicators (journalists, bloggers, editors) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 102 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 23% |
| Student > Master | 14 | 14% |
| Student > Bachelor | 7 | 7% |
| Researcher | 5 | 5% |
| Student > Doctoral Student | 3 | 3% |
| Other | 10 | 10% |
| Unknown | 40 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 39 | 38% |
| Engineering | 11 | 11% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | <1% |
| Business, Management and Accounting | 1 | <1% |
| Mathematics | 1 | <1% |
| Other | 5 | 5% |
| Unknown | 44 | 43% |
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 20 April 2022.
All research outputs
#6,389,497
of 23,570,677 outputs
Outputs from Journal of Cryptographic Engineering
#15
of 65 outputs
Outputs of similar age
#118,753
of 354,716 outputs
Outputs of similar age from Journal of Cryptographic Engineering
#1
of 2 outputs
Altmetric has tracked 23,570,677 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 65 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 72% 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 354,716 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 66% of its contemporaries.
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