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cs.LG2022★ 2 cited
Purifier: Defending Data Inference Attacks via Transforming Confidence Scores
Ziqi Yang, Lijin Wang, Da Yang +5
Neural networks are susceptible to data inference attacks such as the membership inference attack, the adversarial model inversion attack and the attribute inference attack, where…
cs.LG2019
Enhancing Transformation-based Defenses using a Distribution Classifier
Connie Kou, Hwee Kuan Lee, Ee-Chien Chang +1
Adversarial attacks on convolutional neural networks (CNN) have gained significant attention and there have been active research efforts on defense mechanisms. Stochastic input tra…
cs.LG2018
Flipped-Adversarial AutoEncoders
Jiyi Zhang, Hung Dang, Hwee Kuan Lee +1
We propose a flipped-Adversarial AutoEncoder (FAAE) that simultaneously trains a generative model G that maps an arbitrary latent code distribution to a data distribution and an en…