Tutorial Link:
References:
- CVPR 2024: DAP: A Dynamic Adversarial Patch for Evading Person Detectors;
https://arxiv.org/abs/2305.11618 - DAC 2024: ODDR: Outlier Detection & Dimension Reduction Based Defense Against Adversarial Patches; https://arxiv.org/abs/2311.12084
- IEEE Access 2024: SAAM: Stealthy Adversarial Attack on Monocular Depth Estimation; https://ieeexplore.ieee.org/document/10388324
- IEEE Access 2023: Physical Adversarial Attacks for Camera-Based Smart Systems: Current Trends, Categorization, Applications, Research Challenges, and Future Outlook; https://ieeexplore.ieee.org/document/10268441
- MDPI Information 2023: AdvRain: Adversarial Raindrops to Attack Camera-Based Smart Vision Systems; https://www.mdpi.com/2078-2489/14/12/634
- IJCNN 2023: Exploring Machine Learning Privacy/Utility Trade-Off from a
Hyperparameters Lens; https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10191743 - IEEE D&T 2022: SIT: Stochastic Input Transformation to Defend Against Adversarial Attacks on Deep Neural Networks; https://ieeexplore.ieee.org/document/9422778
- IJCNN 2022: ROOM: Adversarial Machine Learning Attacks Under Real-Time
Constraints; https://ieeexplore.ieee.org/document/9892437 - IEEE VTS 2022: Special Session: Towards an Agile Design Methodology for Efficient, Reliable, and Secure ML Systems; https://ieeexplore.ieee.org/document/9794253
- ASPLOS 2021: Defensive approximation: securing CNNs using approximate computing; https://dl.acm.org/doi/abs/10.1145/3445814.3446747