3 papers
cs.CR2026
TimeGuard: Channel-wise Pool Training for Backdoor Defense in Time Series Forecasting
Quang Duc Nguyen, Siyuan Liang, Yiming Li +2
Time Series Forecasting (TSF) is highly vulnerable to backdoor attacks, yet effective defenses remain underexplored due to challenges arising from data entanglement and shifts in t…
cs.CR2026
Cert-SSBD: Certified Backdoor Defense with Sample-Specific Smoothing Noises
Ting Qiao, Yingjia Wang, Xing Liu +3
Deep neural networks (DNNs) are vulnerable to backdoor attacks, where an attacker manipulates a small portion of the training data to implant hidden backdoors into the model. The c…
cs.CR2025
FLARE: Toward Universal Dataset Purification against Backdoor Attacks
Linshan Hou, Wei Luo, Zhongyun Hua +3
Deep neural networks (DNNs) are susceptible to backdoor attacks, where adversaries poison datasets with adversary-specified triggers to implant hidden backdoors, enabling malicious…