FeatureSmith- Learning to Detect Malware by Mining the Security Literature - USENIX Enigma 2017

FeatureSmith- Learning to Detect Malware by Mining the Security Literature - USENIX Enigma 2017

USENIX Enigma Conference via YouTube Direct link

Auto vs. Manual: Features

14 of 18

14 of 18

Auto vs. Manual: Features

Class Central Classrooms beta

YouTube playlists curated by Class Central.

Classroom Contents

FeatureSmith- Learning to Detect Malware by Mining the Security Literature - USENIX Enigma 2017

Automatically move to the next video in the Classroom when playback concludes

  1. 1 Intro
  2. 2 Security and Machine Learning
  3. 3 Running Example: Android Malware Detection • How should we compare samples? - Permissions
  4. 4 Dilemma
  5. 5 Plato's Allegory of the Cave
  6. 6 Challenge #1
  7. 7 Challenge #2
  8. 8 Intuition for Automatic Feature Engineering
  9. 9 Behavior Extraction
  10. 10 Behavior Understanding • Link behaviors to concrete features
  11. 11 Semantic Network Example
  12. 12 How Well Does This Work?
  13. 13 Auto vs. Manual: Experiment
  14. 14 Auto vs. Manual: Features
  15. 15 Auto vs. Manual: Detection Performance
  16. 16 Knowledge Evolution
  17. 17 Alternatives
  18. 18 In A Nutshell

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.