Maxwell’s Demon in MLP-Mixer: towards transferable adversarial attacks
Abstract Models based on MLP-Mixer architecture are becoming popular, but they still suffer from adversarial examples. Although it has been shown that MLP-Mixer is more robust to adversarial attacks compared to convolutional neural networks (CNNs), there has been no research on adversarial attacks t...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2024-03-01
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| Series: | Cybersecurity |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s42400-023-00196-3 |