Data Poisoning Adversarial Data Manipulation Dataset Compromise Malicious Data Tampering Poisoning Attack Training Data Corruption Data Poisoning is a type of adversarial attack where malicious actors intentionally alter or manipulate the training data of a machine learning model to compromise its integrity and performance. This can lead to the model learning incorrect patterns or making erroneous predictions.