190 citations · 316 across the 24 of their papers we have counts for
4 papers · 1 filter
ColorFool: Semantic Adversarial Colorization
Ali Shahin Shamsabadi, Ricardo Sanchez-Matilla, Andrea Cavallaro
Adversarial attacks that generate small L_p-norm perturbations to mislead classifiers have limited success in black-box settings and with unseen classifiers. These attacks are also…
EdgeFool: An Adversarial Image Enhancement Filter
Ali Shahin Shamsabadi, Changjae Oh, Andrea Cavallaro
Adversarial examples are intentionally perturbed images that mislead classifiers. These images can, however, be easily detected using denoising algorithms, when high-frequency spat…
Towards Characterizing and Limiting Information Exposure in DNN Layers
Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas +2
Pre-trained Deep Neural Network (DNN) models are increasingly used in smartphones and other user devices to enable prediction services, leading to potential disclosures of (sensiti…
QUOTIENT: Two-Party Secure Neural Network Training and Prediction
Nitin Agrawal, Ali Shahin Shamsabadi, Matt J. Kusner +1
Recently, there has been a wealth of effort devoted to the design of secure protocols for machine learning tasks. Much of this is aimed at enabling secure prediction from highly-ac…