Attacks against machine learning -- an overview

This blog post survey the attacks techniques that target AI (artificial intelligence) systems and how to protect against them. This post explores each of these classes of attack in turn, providing concrete examples and discussing potential mitigation techniques. This post is the fourth, and last, post in a series of four dedicated to providing a concise overview of how to use AI to build robust anti-abuse protections. The first post explained why AI is key to building robust protection that meets user expectations and increasingly sophisticated attacks. Following the natural progression of building and launching an AI-based defense system, the second post covered the challenges related to training classifiers. The third one looked at the main difficulties faced when using a classifier in production to block attacks.