105 citations · 298 across the 29 of their papers we have counts for
4 papers · 2 filters
Backdoor Attack and Defense for Deep Regression
Xi Li, George Kesidis, David J. Miller +1
We demonstrate a backdoor attack on a deep neural network used for regression. The backdoor attack is localized based on training-set data poisoning wherein the mislabeled samples…
Robust and Active Learning for Deep Neural Network Regression
Xi Li, George Kesidis, David J. Miller +3
We describe a gradient-based method to discover local error maximizers of a deep neural network (DNN) used for regression, assuming the availability of an "oracle" capable of provi…
A BIC-based Mixture Model Defense against Data Poisoning Attacks on Classifiers
Xi Li, David J. Miller, Zhen Xiang +1
Data Poisoning (DP) is an effective attack that causes trained classifiers to misclassify their inputs. DP attacks significantly degrade a classifier's accuracy by covertly injecti…
Anomaly Detection of Adversarial Examples using Class-conditional Generative Adversarial Networks
Hang Wang, David J. Miller, George Kesidis
Deep Neural Networks (DNNs) have been shown vulnerable to Test-Time Evasion attacks (TTEs, or adversarial examples), which, by making small changes to the input, alter the DNN's de…