Content-based Email Filtering

Content-Based Email Filtering is a method of email filtering that analyzes the textual and structural content of email messages—such as keywords, phrases, formatting, and attachments—to distinguish spam or malicious emails from legitimate ones based on intrinsic message features rather than external metadata or sender information.

52

Publications

2.6K

Citations

126

Authors

56

Institutions

Publications per year

2017–2026

5

Authors

126

  1. BB
    Battista Biggio

    University of Cagliari, Italy

    3 publications · 113 citations

    3

    h-index

  2. IP
    Ignazio Pillai

    University of Cagliari, Italy

    3 publications · 113 citations

    3

    h-index

  3. GF
    Giorgio Fumera

    University of Cagliari, Italy

    3 publications · 113 citations

    3

    h-index

  4. FR
    Fabio Roli

    University of Cagliari, Italy

    3 publications · 113 citations

    3

    h-index

  5. QL
    Qiao Liu

    University of Electronic Science and Technology of China, China

    2 publications · 48 citations

    2

    h-index

1–5 of 126

Venues

  1. DSpace@MIT (Massachusetts Institute of Technology)

    Repository · 1 publications · 44 citations

    1

    h-index

  2. 1

    h-index

  3. Artificial Intelligence and Law

    AIL · 1 publications · 17 citations

    1

    h-index

  4. Arrow - TU Dublin (Technological University Dublin)

    Repository · 1 publications · 10 citations

    1

    h-index

  5. Conference on Workshop on Hot Topics in Understanding Botnets

    Conference · 1 publications · 40 citations

    1

    h-index

1–5