Detection Tuning
Detection Tuning is a methodological contribution within the field of cybersecurity threat hunting that refines detection logic and analytical parameters to enhance the precision and efficacy of identifying malicious behaviors while reducing false positives.
5
Publications
167
Citations
19
Authors
8
Institutions
Publications per year
2017–2026
4
Parents
5
Hyeongseok Yu, Ki Ryu, Jieun Park et al. · Dyes and Pigments · 2022 · 26 citations
Bayesian Hyper-Parameter Optimisation for Malware Detection
Fahad T. ALGorain, John A. Clark · Electronics · 2022 · 12 citations · Full text
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8

Universidad de Sevilla
Seville, Spain
1 h-index
4 publications
364 citations
KU Leuven
Leuven, Belgium
1 h-index
3 publications
66 citations
Iowa State University
Ames, United States
1 h-index
3 publications
33 citations

Oakland University
Rochester, United States
1 h-index
3 publications
51 citations
Flanders Make (Belgium)
Lommel, Belgium
1 h-index
3 publications
66 citations

Inha University
Incheon, South Korea
1 h-index
5 publications
130 citations

Universidad de Granada
Granada, Spain
1 h-index
1 publications
91 citations

Ames National Laboratory
Ames, United States
1 h-index
1 publications
11 citations
1–8 of 8
JMP · 1 publications · 22 citations
1
h-index
1 publications · 91 citations
1
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1 publications · 26 citations
1
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IJAI · 1 publications · 11 citations
1 publications · 12 citations
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