Inference Attack

Inference Attack refers to the behavior where an attacker uses the prediction results of a machine learning model to infer sensitive information about the training data. The goal is to reveal data characteristics used during the model training process, including but not limited to individual identities, attribute values, etc. This attack method has significant application value in data privacy protection and security assessment, as it can help identify and fix potential security vulnerabilities, thereby enhancing the overall security of the system. In adversarial machine learning research, Inference Attack is one of the key methods for evaluating the robustness and privacy protection capabilities of models.