Threshold based Technique to Detect Anomalies using Log Files

Author:

David Akande Toluwalope1,Kaur Barjinder2,Dadkhah Sajjad2,Ghorbani Ali A.2

Affiliation:

1. Faculty of Computer Science,UNB, CIC,UNB, Canada

2. Faculty of Computer Science,UNB, UNB, Canada

Publisher

ACM

Reference31 articles.

1. [n.d.]. Cost of downtime. https://www.atlassian.com/incident-management/kpis/cost-of-downtime [n.d.]. Cost of downtime. https://www.atlassian.com/incident-management/kpis/cost-of-downtime

2. [n.d.]. mad. https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.median_abs_deviation.html#scipy.stats.median_abs_deviation [n.d.]. mad. https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.median_abs_deviation.html#scipy.stats.median_abs_deviation

3. Jakub Breier and Jana Branišová . 2015. Anomaly detection from log files using data mining techniques . In Information Science and Applications . Springer , 449–457. Jakub Breier and Jana Branišová. 2015. Anomaly detection from log files using data mining techniques. In Information Science and Applications. Springer, 449–457.

4. A Dynamic Rule Creation Based Anomaly Detection Method for Identifying Security Breaches in Log Records

5. LOF

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