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04/09/2023
CILIATE: Towards Fairer Class-based Incremental Learning by Dataset and Training Refinement
Due to the model aging problem, Deep Neural Networks (DNNs) need updates...
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04/05/2023
UNICORN: A Unified Backdoor Trigger Inversion Framework
The backdoor attack, where the adversary uses inputs stamped with trigge...
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03/23/2023
Detecting Backdoors in Pre-trained Encoders
Self-supervised learning in computer vision trains on unlabeled data, su...
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01/29/2023
Gradient Shaping: Enhancing Backdoor Attack Against Reverse Engineering
Most existing methods to detect backdoored machine learning (ML) models ...
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01/16/2023
BEAGLE: Forensics of Deep Learning Backdoor Attack for Better Defense
Deep Learning backdoor attacks have a threat model similar to traditiona...
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11/29/2022
Backdoor Vulnerabilities in Normally Trained Deep Learning Models
We conduct a systematic study of backdoor vulnerabilities in normally tr...
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10/27/2022
Rethinking the Reverse-engineering of Trojan Triggers
Deep Neural Networks are vulnerable to Trojan (or backdoor) attacks. Rev...
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10/23/2022
FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning
Federated Learning (FL) is a distributed learning paradigm that enables ...
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10/20/2022
Apple of Sodom: Hidden Backdoors in Superior Sentence Embeddings via Contrastive Learning
This paper finds that contrastive learning can produce superior sentence...
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05/26/2022
BppAttack: Stealthy and Efficient Trojan Attacks against Deep Neural Networks via Image Quantization and Contrastive Adversarial Learning
Deep neural networks are vulnerable to Trojan attacks. Existing attacks ...
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04/06/2022
FairNeuron: Improving Deep Neural Network Fairness with Adversary Games on Selective Neurons
With Deep Neural Network (DNN) being integrated into a growing number of...
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02/13/2022
Neural Network Trojans Analysis and Mitigation from the Input Domain
Deep Neural Networks (DNNs) can learn Trojans (or backdoors) from benign...
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02/11/2022
Constrained Optimization with Dynamic Bound-scaling for Effective NLPBackdoor Defense
We develop a novel optimization method for NLPbackdoor inversion. We lev...
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12/06/2021
Fast Test Input Generation for Finding Deviated Behaviors in Compressed Deep Neural Network
Model compression can significantly reduce sizes of deep neural network ...
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03/16/2021
EX-RAY: Distinguishing Injected Backdoor from Natural Features in Neural Networks by Examining Differential Feature Symmetry
Backdoor attack injects malicious behavior to models such that inputs em...
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02/09/2021
Backdoor Scanning for Deep Neural Networks through K-Arm Optimization
Back-door attack poses a severe threat to deep learning systems. It inje...
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12/21/2020
Deep Feature Space Trojan Attack of Neural Networks by Controlled Detoxification
Trojan (backdoor) attack is a form of adversarial attack on deep neural ...
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07/16/2020
Deep Learning Backdoors
Intuitively, a backdoor attack against Deep Neural Networks (DNNs) is to...
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06/01/2020
BadNL: Backdoor Attacks Against NLP Models
Machine learning (ML) has progressed rapidly during the past decade and ...
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03/07/2020
Dynamic Backdoor Attacks Against Machine Learning Models
Machine learning (ML) has made tremendous progress during the past decad...
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09/06/2019
Testing Deep Learning Models for Image Analysis Using Object-Relevant Metamorphic Relations
Deep learning models are widely used for image analysis. While they offe...
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10/27/2018
