3 papers
cs.CV2026
Giving AI a Headache: Acoustic Adversarial Attacks to Computer Vision Applications
Nicole Villavicencio-Garduño, Maksim Ekin Eren, Milo Prisbrey +2
Artificial Intelligence (AI) is increasingly used to automate a variety of real-world computer vision (CV) applications, such as autonomous vehicle control, facial recognition, and…
cs.CV2024
Improving Robustness to Model Inversion Attacks via Sparse Coding Architectures
Sayanton V. Dibbo, Adam Breuer, Juston Moore +1
Recent model inversion attack algorithms permit adversaries to reconstruct a neural network's private and potentially sensitive training data by repeatedly querying the network. In…
cs.LG2024
How Robust Are Energy-Based Models Trained With Equilibrium Propagation?
Siddharth Mansingh, Michal Kucer, Garrett Kenyon +2
Deep neural networks (DNNs) are easily fooled by adversarial perturbations that are imperceptible to humans. Adversarial training, a process where adversarial examples are added to…