Mastering Machine Learning for Penetration Testing

Chapter 9 – Bypass Machine Learning Malware Detectors

1. What are the components of generative adversarial networks?

The two main components of a generative adversarial network are the generator and the discriminator.

2. What is the difference between a generator and a discriminator?

The generator takes latent samples as input. They are randomly generated numbers and they are trained to generate images, while the discriminator is simply a classifier trained with supervised learning techniques to check whether the image is real (1) or fake (0).

3. How can we make sure that the malware adversarial samples are still valid when we are generating them?

To avoid invalid samples, we can use a Sandbox/Oracle.

4. Do a bit of research, then briefly ...