CSGSG
Rahul Duggal
Sihang Liu's Homepage
I am a research scientist at Intel Labs, doing research on Adversarial Machine learning. I earned my Ph.D. degree in Computer Science at the University of Virginia in May 2019, co-advised by Prof. David Evans and Prof. Yanjun Qi . Previously I was an engineer at NISL , Tsinghua University. Here's my Google Scholar profile. Email: weilinuva gmail.com
We propose a new strategy, feature squeezing, that can be used to harden DNN models by detecting adversarial examples. Feature squeezing reduces the search space available to an adversary by coalescing similar samples that correspond to many different feature vectors in the original space into a single sample.
Machine learning is widely used to develop classifiers for security tasks. However, the robustness of these methods against motivated adversaries is uncertain. In this work, we propose a generic method to evaluate the robustness of classifiers under attack. The key idea is to stochastically manipulate a malicious sample to find a variant that preserves the malicious behavior but is classified as benign by the classifier. We present a general approach to search for evasive variants and report on results from
CSGSG
Rahul Duggal
Sihang Liu's Homepage