2 papers
cs.LG2019
Deep Detector Health Management under Adversarial Campaigns
Javier Echauz, Keith Kenemer, Sarfaraz Hussein +4
Machine learning models are vulnerable to adversarial inputs that induce seemingly unjustifiable errors. As automated classifiers are increasingly used in industrial control system…
cs.CV2018
Gradient Similarity: An Explainable Approach to Detect Adversarial Attacks against Deep Learning
Jasjeet Dhaliwal, Saurabh Shintre
Deep neural networks are susceptible to small-but-specific adversarial perturbations capable of deceiving the network. This vulnerability can lead to potentially harmful consequenc…