  This paper extensively evaluates the vulnerability of capsule networks to
different adversarial attacks. Recent work suggests that these architectures
are more robust towards adversarial attacks than other neural networks.
However, our experiments show that capsule networks can be fooled as easily as
convolutional neural networks.

Machine Learning;Cryptography and Security;Machine Learning