The Future Prospects of Adversarial Nets.

Machine learning has obtained remarkable achievement in longstanding tasks in various domains of artificial intelligence. However, machine learning certainly has some security threats, such as adversarial examples that hamper the machine learning models from correctly classifying the data. The adversarial examples are minor perturbations in the actual inputs to detract the model from its original task. Adversarial Attacks and their defenses are found in parallel when it comes to the literature of machine learning adversaries. In this paper, we have tried to inspect the adversarial attack types and their defenses by comprehensively classifying different techniques.