Log Correlation Rules

Log Correlation Rules is a formal method in log management that identifies and establishes temporal, causal, or contextual relationships among discrete log entries across heterogeneous systems to detect complex events or patterns indicative of specific system behaviors or security incidents.

9

Publications

266

Citations

15

Authors

8

Institutions

Publications per year

2017–2026

3

Authors

15

  1. DF
    Dario Forte

    University of Milan, Italy

    2 publications · 35 citations

    2

    h-index

  2. FM
    Fabrizio Marozzo

    University of Calabria, Italy

    1 publications · 36 citations

    1

    h-index

  3. DT
    Domenico Talia

    University of Calabria, Italy

    1 publications · 36 citations

    1

    h-index

  4. HM
    Hafiz M. Farooq

    1 publications · 54 citations

    1

    h-index

  5. JP
    John P. Rouillard

    University of Massachusetts Boston, United States

    1 publications · 65 citations

    1

    h-index

1–5 of 15

Venues

  1. Computer Fraud & Security

    2 publications · 35 citations

    2

    h-index

  2. Big Data and Cognitive Computing

    1 publications · 36 citations

    1

    h-index

  3. Journal of Chromatography A

    1 publications · 24 citations

    1

    h-index

  4. Mathematical Geology

    1 publications · 13 citations

    1

    h-index

  5. SPE Formation Evaluation

    1 publications · 19 citations

    1

    h-index

1–5