Practical Cyborgism - Machine Learning for Bro Logs

Practical Cyborgism - Machine Learning for Bro Logs

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Intro

1 of 21

1 of 21

Intro

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Practical Cyborgism - Machine Learning for Bro Logs

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  1. 1 Intro
  2. 2 A story we all know: Regular expressions
  3. 3 When's the last time you heard...?
  4. 4 Problem Statement: HTTP Proxy Logs
  5. 5 Machine Assisted Analysis
  6. 6 Two different types of machine learning
  7. 7 Supervised: Binary Classification
  8. 8 Classification With Random Forests
  9. 9 Generating synthetic abnormal data
  10. 10 Decision Trees
  11. 11 Unsupervised: Outlier Detection
  12. 12 Isolation Forests Liu, Ting, Zhao
  13. 13 A quick note about parameters
  14. 14 Classification With Isolation Forests
  15. 15 The beauty of scikit leam & python
  16. 16 Identifying Training & Test Data
  17. 17 Training, Testing & Evaluating a Model
  18. 18 Bonus: Most influential Features with
  19. 19 Analyzing Log Files
  20. 20 Bonus: Classifier Explanations with
  21. 21 Ideas for improvement

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