Nikita Samarin

Evading classifiers in discrete domains with provable optimality guarantees

2018 · arXiv (Cornell University)

Machine-learning models for security-critical applications such as bot, malware, or spam detection, operate in constrained discrete domains. These applications would benefit from having provable guarantees against adversarial examples. The existing literature on provable adversarial robustness …