👉 A label weapon is a type of AI model or technique that generates misleading or false labels to manipulate the behavior of other machine learning models, particularly in supervised learning scenarios. By providing incorrect or strategically crafted labels to a model during training, an attacker can cause the model to learn and propagate these false labels, leading to biased predictions or misclassifications that benefit the attacker. This concept is often used in adversarial attacks, where the goal is to exploit vulnerabilities in models to achieve specific outcomes, such as misclassifying images or altering predictions. Label weapons can be particularly dangerous in critical applications like healthcare, autonomous driving, and security systems, where incorrect labels could have severe real-world consequences.
