178 citations · 347 across the 23 of their papers we have counts for
6 papers · 1 filter
PubDef: Defending Against Transfer Attacks From Public Models
Chawin Sitawarin, Jaewon Chang, David Huang +2
Adversarial attacks have been a looming and unaddressed threat in the industry. However, through a decade-long history of the robustness evaluation literature, we have learned that…
Adversarial Examples for -Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams
Chawin Sitawarin, Evgenios M. Kornaropoulos, Dawn Song +1
Adversarial examples are a widely studied phenomenon in machine learning models. While most of the attention has been focused on neural networks, other practical models also suffer…
Minimum-Norm Adversarial Examples on KNN and KNN-Based Models
Chawin Sitawarin, David Wagner
We study the robustness against adversarial examples of kNN classifiers and classifiers that combine kNN with neural networks. The main difficulty lies in the fact that finding an…
SAT: Improving Adversarial Training via Curriculum-Based Loss Smoothing
Chawin Sitawarin, Supriyo Chakraborty, David Wagner
Adversarial training (AT) has become a popular choice for training robust networks. However, it tends to sacrifice clean accuracy heavily in favor of robustness and suffers from a…
Defending Against Adversarial Examples with K-Nearest Neighbor
Chawin Sitawarin, David Wagner
Robustness is an increasingly important property of machine learning models as they become more and more prevalent. We propose a defense against adversarial examples based on a k-n…
Better the Devil you Know: An Analysis of Evasion Attacks using Out-of-Distribution Adversarial Examples
Vikash Sehwag, Arjun Nitin Bhagoji, Liwei Song +4
A large body of recent work has investigated the phenomenon of evasion attacks using adversarial examples for deep learning systems, where the addition of norm-bounded perturbation…