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Backdoor Attacks on Vision Transformers. (arXiv:2206.08477v1 [cs.CV])
June 20, 2022, 1:20 a.m. | Akshayvarun Subramanya, Aniruddha Saha, Soroush Abbasi Koohpayegani, Ajinkya Tejankar, Hamed Pirsiavash
cs.CR updates on arXiv.org arxiv.org
Vision Transformers (ViT) have recently demonstrated exemplary performance on
a variety of vision tasks and are being used as an alternative to CNNs. Their
design is based on a self-attention mechanism that processes images as a
sequence of patches, which is quite different compared to CNNs. Hence it is
interesting to study if ViTs are vulnerable to backdoor attacks. Backdoor
attacks happen when an attacker poisons a small part of the training data for
malicious purposes. The model performance is …
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