Adversarial Attacks and Defences: A Survey

Understand

Deep learning has emerged as a strong and efficient framework that can be applied to a broad spectrum of complex learning problems which were difficult to solve using the traditional machine learning techniques in the past.

• In the last few years, deep learning has advanced radically in such a way that it can surpass human-level performance on a number of tasks.
• As a consequence, deep learning is being extensively used in most of the recent day-to-day applications.
• However, security of deep learning systems are vulnerable to crafted adversarial examples, which may be imperceptible to the human eye, but can lead the model to misclassify the output.