👉 The Regression Weapon is a type of adversarial machine learning attack where an attacker manipulates input data to cause a machine learning model to regress or behave unpredictably, often leading to incorrect predictions or outputs. This is typically achieved by subtly altering legitimate input data in a way that the model's learned patterns or decision boundaries are exploited, causing it to produce erroneous results. For example, in image classification tasks, an attacker might introduce slight perturbations to images that are imperceptible to humans but lead the model to misclassify them. The Regression Weapon exploits vulnerabilities in the model's sensitivity to input changes, highlighting the need for robust and resilient machine learning systems.
