The similarity between poisonous data and adversarial attacks (adversarial-designs.shop)

Data poisoning is when someone adds small changes to a training dataset to cause any model trained on those data to misbehave. An effective heuristic approach involves generating adversarial examples instead. The authors show degradations in model accuracy that are worse than random chance performance.