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08/04/2023
ParaFuzz: An Interpretability-Driven Technique for Detecting Poisoned Samples in NLP
Backdoor attacks have emerged as a prominent threat to natural language ...
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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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01/16/2023
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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10/23/2022
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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06/18/2022
DECK: Model Hardening for Defending Pervasive Backdoors
Pervasive backdoors are triggered by dynamic and pervasive input perturb...
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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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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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01/22/2020
PENet: Object Detection using Points Estimation in Aerial Images
Aerial imagery has been increasingly adopted in mission-critical tasks, ...
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10/06/2019
