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What are the components of generative adversarial networks?
The two main components of a generative adversarial network are the generator and the discriminator.
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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).
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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.
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Do a bit of research, then briefly explain how to detect adversarial samples
To detect adversarial samples, we can remove the noise by using binary thresholding.
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