Towards verifying robustness of neural networks against a family of semantic perturbations
Verifying robustness of neural networks given a specified threat model is a fundamental yet challenging task. While current verification methods mainly focus on the p-norm threat model of the input instances, robustness verification against semantic adversarial attacks inducing large p-norm perturba...
| Main Authors: | , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
IEEE,
2021-02-25T15:17:24Z.
|
| Subjects: | |
| Online Access: | Get fulltext |