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Featured Co-authors

Bo Li
461 publications
Xi Li
111 publications
Siheng Chen
75 publications
George Kesidis
41 publications
David J. Miller
23 publications
Hang Wang
22 publications
Pedro Gonnet
6 publications
Xinyi Hu
6 publications
Matthieu Schaller
4 publications
James S. Willis
3 publications
Peter W. Draper
3 publications

∙ 08/18/2023

Backdoor Mitigation by Correcting the Distribution of Neural Activations

Backdoor (Trojan) attacks are an important type of adversarial exploit a...

0 Xi Li, et al. ∙

∙ 08/08/2023

Improved Activation Clipping for Universal Backdoor Mitigation and Test-Time Detection

Deep neural networks are vulnerable to backdoor attacks (Trojans), where...

0 Hang Wang, et al. ∙

∙ 05/29/2023

UMD: Unsupervised Model Detection for X2X Backdoor Attacks

Backdoor (Trojan) attack is a common threat to deep neural networks, whe...

0 Zhen Xiang, et al. ∙

∙ 05/22/2023

Swift: A modern highly-parallel gravity and smoothed particle hydrodynamics solver for astrophysical and cosmological applications

Numerical simulations have become one of the key tools used by theorists...

0 Matthieu Schaller, et al. ∙

∙ 05/13/2022

Universal Post-Training Backdoor Detection

A Backdoor attack (BA) is an important type of adversarial attack agains...

0 Hang Wang, et al. ∙

∙ 01/20/2022

Post-Training Detection of Backdoor Attacks for Two-Class and Multi-Attack Scenarios

Backdoor attacks (BAs) are an emerging threat to deep neural network cla...

0 Zhen Xiang, et al. ∙

∙ 12/06/2021

Test-Time Detection of Backdoor Triggers for Poisoned Deep Neural Networks

Backdoor (Trojan) attacks are emerging threats against deep neural netwo...

0 Xi Li, et al. ∙

∙ 10/20/2021

Detecting Backdoor Attacks Against Point Cloud Classifiers

Backdoor attacks (BA) are an emerging threat to deep neural network clas...

0 Zhen Xiang, et al. ∙

∙ 05/28/2021

A BIC based Mixture Model Defense against Data Poisoning Attacks on Classifiers

Data Poisoning (DP) is an effective attack that causes trained classifie...

0 Xi Li, et al. ∙

∙ 04/12/2021

A Backdoor Attack against 3D Point Cloud Classifiers

Vulnerability of 3D point cloud (PC) classifiers has become a grave conc...

0 Zhen Xiang, et al. ∙

∙ 10/20/2020

L-RED: Efficient Post-Training Detection of Imperceptible Backdoor Attacks without Access to the Training Set

Backdoor attacks (BAs) are an emerging form of adversarial attack typica...

0 Zhen Xiang, et al. ∙

∙ 10/15/2020

Reverse Engineering Imperceptible Backdoor Attacks on Deep Neural Networks for Detection and Training Set Cleansing

Backdoor data poisoning is an emerging form of adversarial attack usuall...

0 Zhen Xiang, et al. ∙

∙ 11/18/2019

Revealing Perceptible Backdoors, without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic

Recently, a special type of data poisoning (DP) attack, known as a backd...

0 Zhen Xiang, et al. ∙

∙ 08/27/2019

Revealing Backdoors, Post-Training, in DNN Classifiers via Novel Inference on Optimized Perturbations Inducing Group Misclassification

Recently, a special type of data poisoning (DP) attack targeting Deep Ne...

1 Zhen Xiang, et al. ∙

∙ 04/12/2019

Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks

With the wide deployment of machine learning (ML) based systems for a va...

0 David J. Miller, et al. ∙

∙ 10/31/2018

A Mixture Model Based Defense for Data Poisoning Attacks Against Naive Bayes Spam Filters

Naive Bayes spam filters are highly susceptible to data poisoning attack...

0 David J. Miller, et al. ∙

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