Targeted Adversarial Attacks against Neural Machine Translation. (arXiv:2303.01068v1 [cs.CL])

Neural Machine Translation (NMT) systems are used in various applications.
However, it has been shown that they are vulnerable to very small perturbations
of their inputs, known as adversarial attacks. In this paper, we propose a new
targeted adversarial attack against NMT models. In particular, our goal is to
insert a predefined target keyword into the translation of the adversarial
sentence while maintaining similarity between the original sentence and the
perturbed one in the source domain. To this aim, we …

adversarial adversarial attacks applications attack attacks inputs machine similarity systems target vulnerable