{"iri":"http://lmss.sali.org/RBMj5dbvLFgFGrPZ3MvFGYl","id":"RBMj5dbvLFgFGrPZ3MvFGYl","label":"Data Poisoning","definition":"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.","prefLabels":[],"altLabels":["Adversarial Data Manipulation","Dataset Compromise","Malicious Data Tampering","Poisoning Attack","Training Data Corruption"],"examples":[],"notes":[],"sources":[],"branch":{"iri":"http://lmss.sali.org/R9B8sRCK209t5Y8LlU4f62a","label":"Legal Use Cases"},"parents":[{"iri":"http://lmss.sali.org/RBHMad8oNmYXkYHOHZLCgqv","id":"RBHMad8oNmYXkYHOHZLCgqv","label":"AI Lifecycle Systems"}],"children":[],"relations":[],"url":"https://lmss.io/tag/RBMj5dbvLFgFGrPZ3MvFGYl/","source":{"repo":"sali-legal/LMSS","ref":"3f9ac0c9357b2a971582ae79ede243511d47811d","channel":"pre-release"}}