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Classroom Contents
Model-Reuse Attacks on Deep Learning Systems
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- 1 Intro
- 2 Machine Learning in Our Daily Lives
- 3 Ever-increasing Model Complexity
- 4 Pre-trained Models as Building Blocks
- 5 Are Pre-trained Models Safe?
- 6 Model-Reuse Attacks
- 7 Attack Setting
- 8 Attack Objectives
- 9 Generating Semantic Neighbors
- 10 Finding Salient Features
- 11 Crafting Adversarial Models
- 12 Case Studies
- 13 Multi-view Autonomous Steering
- 14 Experimental Setting
- 15 Attack Effectiveness
- 16 Attack Evasiveness
- 17 Other Experiments
- 18 Summary
