A Survey on Machine Learning Adversarial Attacks
Flávio Luís de Mello · Journal of Information Security and Cryptography (Enigma) · 2020
It is becoming notorious several types of adversaries based on their threat model leverage vulnerabilities to compromise a machine learning system. Therefore, it is important to provide robustness to machine learning algorithms and systems against these adversaries. However, there are only a few strong countermeasures, which can be used in all types of attack scenarios to design a robust artificial intelligence system. This paper is structured and comprehensive overview of the research on attacks to machine learning systems and it tries to call the attention from developers and software houses to the security issues concerning machine learning.