What Is Data Poisoning? How Attackers Corrupt AI Models and Datasets

Data poisoning involves manipulating AI training or evaluation data to induce corrupted behavior or attacker-chosen outputs. It requires identifiable input, a characteristic transformation, and an evaluable outcome. This guide clarifies its definition, boundaries, and operational stages, distinguishing it from evasion attacks.