23 citations · 60 across the 17 of their papers we have counts for
5 papers · 1 filter
Post-Training Detection of Backdoor Attacks for Two-Class and Multi-Attack Scenarios
Zhen Xiang, David J. Miller, George Kesidis
Backdoor attacks (BAs) are an emerging threat to deep neural network classifiers. A victim classifier will predict to an attacker-desired target class whenever a test sample is emb…
Test-Time Detection of Backdoor Triggers for Poisoned Deep Neural Networks
Xi Li, Zhen Xiang, David J. Miller +1
Backdoor (Trojan) attacks are emerging threats against deep neural networks (DNN). A DNN being attacked will predict to an attacker-desired target class whenever a test sample from…
Detecting Backdoor Attacks Against Point Cloud Classifiers
Zhen Xiang, David J. Miller, Siheng Chen +2
Backdoor attacks (BA) are an emerging threat to deep neural network classifiers. A classifier being attacked will predict to the attacker's target class when a test sample from a s…
A Backdoor Attack against 3D Point Cloud Classifiers
Zhen Xiang, David J. Miller, Siheng Chen +2
Vulnerability of 3D point cloud (PC) classifiers has become a grave concern due to the popularity of 3D sensors in safety-critical applications. Existing adversarial attacks agains…
A Mixture Model Based Defense for Data Poisoning Attacks Against Naive Bayes Spam Filters
David J. Miller, Xinyi Hu, Zhen Xiang +1
Naive Bayes spam filters are highly susceptible to data poisoning attacks. Here, known spam sources/blacklisted IPs exploit the fact that their received emails will be treated as (…