382 citations · 2.5k across the 96 of their papers we have counts for
4 papers · 2 filters
PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier
Chong Xiang, Saeed Mahloujifar, Prateek Mittal
The adversarial patch attack against image classification models aims to inject adversarially crafted pixels within a restricted image region (i.e., a patch) for inducing model mis…
PatchGuard++: Efficient Provable Attack Detection against Adversarial Patches
Chong Xiang, Prateek Mittal
An adversarial patch can arbitrarily manipulate image pixels within a restricted region to induce model misclassification. The threat of this localized attack has gained significan…
SSD: A Unified Framework for Self-Supervised Outlier Detection
Vikash Sehwag, Mung Chiang, Prateek Mittal
We ask the following question: what training information is required to design an effective outlier/out-of-distribution (OOD) detector, i.e., detecting samples that lie far away fr…
DetectorGuard: Provably Securing Object Detectors against Localized Patch Hiding Attacks
Chong Xiang, Prateek Mittal
State-of-the-art object detectors are vulnerable to localized patch hiding attacks, where an adversary introduces a small adversarial patch to make detectors miss the detection of…