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

Authors

4.7K

  1. QL
    Qi Li

    Tsinghua University, China

    9 publications · 654 citations

    9

    h-index

  2. KX
    Ke Xu

    Tsinghua University, China

    8 publications · 668 citations

    8

    h-index

  3. GA
    Giovanni Apruzzese

    University of Modena and Reggio Emilia, Italy

    8 publications · 691 citations

    8

    h-index

  4. MC
    Mauro Conti

    University of Padua, Italy

    7 publications · 619 citations

    7

    h-index

  5. SS
    Stefan Savage

    University of California San Diego, United States

    7 publications · 978 citations

    7

    h-index

1–5 of 4.7K

Venues

  1. IEEE Access

    62 publications · 4.2K citations

    35

    h-index

  2. Computers & Security

    26 publications · 1.6K citations

    22

    h-index

  3. Sensors

    33 publications · 1.9K citations

    22

    h-index

  4. IEEE Internet of Things Journal

    25 publications · 2.9K citations

    21

    h-index

  5. 21

    h-index

1–5