Rules-based Detection Systems

Rules-Based Detection Systems is a detection methodology that identifies suspicious activities by applying a predefined set of logical rules or heuristics to observed behaviors, distinguishing it from statistical or machine learning approaches through its reliance on explicit, human-encoded domain knowledge.

132

Publications

5.4K

Citations

398

Authors

187

Institutions

Publications per year

2017–2026

44

Authors

398

  1. AO
    Ali Ouni

    École de Technologie Supérieure, Canada

    4 publications · 305 citations

    4

    h-index

  2. MK
    Marouane Kessentini

    University of Michigan–Dearborn, United States

    3 publications · 190 citations

    3

    h-index

  3. IS
    I. S. A. Pereira

    Universidade Federal do Espírito Santo, Brazil

    3 publications · 62 citations

    3

    h-index

  4. NN
    Nitin Naik

    Ministry of Defence, United Kingdom

    3 publications · 163 citations

    3

    h-index

  5. PJ
    Paul Jenkins

    Ministry of Defence, United Kingdom

    2 publications · 47 citations

    2

    h-index

1–5 of 398

Venues

  1. Procedia Computer Science

    4 publications · 187 citations

    4

    h-index

  2. Expert Systems with Applications

    4 publications · 243 citations

    4

    h-index

  3. 2

    h-index

  4. IBM Journal of Research and Development

    2 publications · 325 citations

    2

    h-index

  5. IEEE Transactions on Fuzzy Systems

    TFS · 2 publications · 130 citations

    2

    h-index

1–5