Does Few-Shot Learning Suffer from Backdoor Attacks?
Xinwei Liu,
Xiaojun Jia,
Jindong Gu
et al.
Abstract:The field of few-shot learning (FSL) has shown promising results in scenarios where training data is limited, but its vulnerability to backdoor attacks remains largely unexplored. We first explore this topic by first evaluating the performance of the existing backdoor attack methods on few-shot learning scenarios. Unlike in standard supervised learning, existing backdoor attack methods failed to perform an effective attack in FSL due to two main issues. Firstly, the model tends to overfit to either benign feat… Show more
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