Data Poisoning: Current Trends and Recommended Defense Strategies - wiz.io

Data poisoning is an adversarial attack that manipulates AI and machine learning model training datasets by injecting, modifying, or deleting data to degrade model performance or induce specific malicious behaviors. This can lead to critical impacts such as biased decision-making, compromised predictive accuracy, system failures, and the creation of backdoor vulnerabilities within AI-driven systems.