How does Random Forest behave under adversarial label flipping attacks?

RF is robust to random label flips but vulnerable to targeted adversarial flips.

Random label flips introduce noise that is averaged out across trees. However, adversarial flips targeting influential regions of feature space can distort impurity calculations, leading to systematic bias in splits. This degrades ensemble performance disproportionately.