How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses

Deep Learning is currently used to perform multiple tasks, such as object recognition, face recognition, and natural language processing. However, Deep Neural Networks (DNNs) are vulnerable to perturbations that alter the network prediction, named adversarial examples, which raise concerns regarding the usage of DNNs in critical areas, such as Self-driving Vehicles, Malware Detection, and Healthcare. This paper compiles the most recent adversarial attacks in Object Recognition, grouped by the attacker capacity and knowledge, and modern defenses clustered by protection strategies, providing background details to understand the topic of adversarial attacks and defenses. The new advances regarding Vision…