Malicious Traffic Detection
Malicious Traffic Detection is a technical framework within the domain of network security that identifies and analyzes anomalous or harmful data transmissions by distinguishing potentially adversarial network activities from benign traffic through signature-based, behavior-based, or machine learning-driven methodologies.
1.5K
Publications
78K
Citations
4.7K
Authors
1.4K
Institutions
Publications per year
2017–2026
1K
Parents
1.5K
Developing Realistic Distributed Denial of Service (DDoS) Attack Dataset and Taxonomy
Iman Sharafaldin, Arash Habibi Lashkari, Saqib Hakak et al. · 2019 · 1.1K citations
Fast portscan detection using sequential hypothesis testing
Jaeyeon Jung, Vern Paxson, Arno Berger et al. · 2004 · 670 citations
1–5 of 1.5K
4.7K
9
h-index
8
h-index
8
h-index
7
h-index
7
h-index
1–5 of 4.7K
1.4K

Chinese Academy of Sciences
Beijing, China
18 h-index
83 publications
2.8K citations
University of Chinese Academy of Sciences
Beijing, China
17 h-index
94 publications
2.6K citations

King Saud University
Riyadh, Saudi Arabia
16 h-index
36 publications
3.2K citations

Beijing University of Posts and Telecommunications
Beijing, China
15 h-index
52 publications
2.1K citations
Tsinghua University
Beijing, China
15 h-index
62 publications
4.3K citations
Institute of Information Engineering
Beijing, China
15 h-index
85 publications
2.7K citations

Beijing Institute of Technology
Beijing, China
12 h-index
30 publications
1.2K citations
Georgia Institute of Technology
Atlanta, United States
12 h-index
34 publications
6.3K citations
1–8 of 1.4K
62 publications · 4.2K citations
35
h-index
26 publications · 1.6K citations
22
h-index
33 publications · 1.9K citations
22
h-index
25 publications · 2.9K citations
21
h-index
25 publications · 1.7K citations
21
h-index
1–5