Adversarial Attacks on Neural Models of Code via Code Difference Reduction. (arXiv:2301.02412v1 [cs.CR])

Deep learning has been widely used to solve various code-based tasks by
building deep code models based on a large number of code snippets. However,
deep code models are still vulnerable to adversarial attacks. As source code is
discrete and has to strictly stick to the grammar and semantics constraints,
the adversarial attack techniques in other domains are not applicable.
Moreover, the attack techniques specific to deep code models suffer from the
effectiveness issue due to the enormous attack space. …

adversarial adversarial attacks attack attacks attack techniques code constraints deep learning domains large snippets source code techniques vulnerable