Protecting AI Systems Against Data Poisoning

Data poisoning—where adversaries tamper with training data to corrupt model behavior—poses significant risks as AI adoption expands across critical sectors. Organizations without mechanisms in place to detect or prevent data poisoning are open to an avenue of attack that, once exploited, is difficult to remedi ate . Machine unlearning and model retraining are not always viable or effective…