Summary

After reading this chapter, you should understand how attacks can be perpetrated on machine learning models and evasion attacks in particular. You should know how to perform FSGM, BIM, PGD, C&W, and AP attacks, as well as how to defend against them with spatial smoothing and adversarial training. Last but not least, you know how to evaluate adversarial robustness.

The next chapter is the last one, and it outlines some ideas on what’s next for machine learning interpretation.