Visualizing Poisoning

How does a poisoning attack work and why are some groups more susceptible to being victimized by a poisoning attack?

We’ve posted work that helps understand how poisoning attacks work with some engaging visualizations:

Poisoning Attacks and Subpopulation Susceptibility
An Experimental Exploration on the Effectiveness of Poisoning Attacks
Evan Rose, Fnu Suya, and David Evans

Follow the link to try the interactive version!

Machine learning is susceptible to poisoning attacks in which adversaries inject maliciously crafted training data into the training set to induce specific model behavior. We focus on subpopulation attacks, in which the attacker’s goal is to induce a model that produces a targeted and incorrect output (label blue in our demos) for a particular subset of the input space (colored orange). We study the question, which subpopulations are the most vulnerable to an attack and why?