Corpus ID: 231632260

Red Alarm for Pre-trained Models: Universal Vulnerabilities by Neuron-Level Backdoor Attacks

@article{Zhang2021RedAF,
  title={Red Alarm for Pre-trained Models: Universal Vulnerabilities by Neuron-Level Backdoor Attacks},
  author={Zhengyan Zhang and Guangxuan Xiao and Yongwei Li and Tian Lv and Fanchao Qi and Yasheng Wang and Xin Jiang and Zhiyuan Liu and Maosong Sun},
  journal={ArXiv},
  year={2021},
  volume={abs/2101.06969}
}
Pre-trained models (PTMs) have been widely used in various downstream tasks. The parameters of PTMs are distributed on the Internet and may suffer backdoor attacks. In this work, we demonstrate the universal vulnerability of PTMs, where fine-tuned PTMs can be easily controlled by backdoor attacks in arbitrary downstream tasks. Specifically, attackers can add a simple pre-training task, which restricts the output representations of trigger instances to pre-defined vectors, namely neuron-level… Expand

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