Use the Spear as a Shield: An Adversarial Example Based Privacy-Preserving Technique Against Membership Inference Attacks
Use the Spear as a Shield: An Adversarial Example Based Privacy-Preserving Technique Against Membership Inference Attacks
Recently, the membership inference attack poses a serious threat to the privacy of confidential training data of machine learning models. This paper proposes a novel adversarial example based privacy-preserving technique (AEPPT), which adds the crafted adversarial perturbations to the prediction of the target model to mislead the adversary's membership inference …