Backdoor (Trojan) attacks are an important type of adversarial exploit
a...
Deep neural networks are vulnerable to backdoor attacks (Trojans), where...
A Backdoor attack (BA) is an important type of adversarial attack agains...
Backdoor attacks (BAs) are an emerging threat to deep neural network
cla...
Backdoor (Trojan) attacks are emerging threats against deep neural netwo...
Backdoor attacks (BA) are an emerging threat to deep neural network
clas...
We demonstrate a backdoor attack on a deep neural network used for
regre...
We describe a gradient-based method to discover local error maximizers o...
Data Poisoning (DP) is an effective attack that causes trained classifie...
Deep Neural Networks (DNNs) have been shown vulnerable to adversarial
(T...
Vulnerability of 3D point cloud (PC) classifiers has become a grave conc...
Backdoor attacks (BAs) are an emerging form of adversarial attack typica...
Backdoor data poisoning is an emerging form of adversarial attack usuall...
Recently, a special type of data poisoning (DP) attack, known as a backd...
We provide a local class purity theorem for Lipschitz continuous,
half-r...
Recently, a special type of data poisoning (DP) attack targeting Deep Ne...
With the wide deployment of machine learning (ML) based systems for a va...
Naive Bayes spam filters are highly susceptible to data poisoning attack...
This paper addresses detection of a reverse engineering (RE) attack targ...
A significant threat to the recent, wide deployment of machine learning-...
We propose an algorithm for detecting patterns exhibited by anomalous
cl...
Blind Source Separation (BSS) has proven to be a powerful tool for the
a...
We propose a parsimonious topic model for text corpora. In related model...