Adversarial Robustness of Vision Transformers: A Comprehensive Study
Araş. Gör. Mehmet Can, Dr. Ayşe Korkmaz
YTU Journal of Computer Science· Vol. 12 (1)· pp. 45-62· 18 February 2026· https://doi.org/10.5555/ytu.2026.002
Abstract
We present a comprehensive evaluation of adversarial robustness across various Vision Transformer architectures and compare them with CNN-based models.
Keywords
adversarial robustnessvision transformersdeep learningcomputer vision
How to cite
Araş. Gör. Mehmet Can, Dr. Ayşe Korkmaz (2026). Adversarial Robustness of Vision Transformers: A Comprehensive Study. YTU Journal of Computer Science, 12(1), 45-62. https://doi.org/10.5555/ytu.2026.002
© 2026 the author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence.