Detecting Security Hazards in SEAndroid Vendor Customizations via Large-Scale Supervised ML

Detecting Security Hazards in SEAndroid Vendor Customizations via Large-Scale Supervised ML

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P9 Rules

15 of 24

15 of 24

P9 Rules

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Detecting Security Hazards in SEAndroid Vendor Customizations via Large-Scale Supervised ML

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  1. 1 Introduction
  2. 2 Framework
  3. 3 Policy Language
  4. 4 Android is complex
  5. 5 Winter customizations
  6. 6 Our work
  7. 7 Key idea
  8. 8 Architecture
  9. 9 Strategy
  10. 10 Differential Analysis
  11. 11 Never Allowed
  12. 12 Combine
  13. 13 Special Symbols
  14. 14 Critical Fields
  15. 15 P9 Rules
  16. 16 Training Set
  17. 17 Feature Extraction
  18. 18 Model Training
  19. 19 CrossValidation
  20. 20 Results
  21. 21 Data Acquisition
  22. 22 Example
  23. 23 Summary
  24. 24 Showcase

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