Privacy

How Does Data Augmentation Affect Privacy in Machine Learning? AAAI 2021 IronMask: Modular Architecture for Protecting Deep Face Template CVPR 2021 Knowledge-Enriched Distributional Model Inversion Attacks ICCV 2021 Label-Only Membership Inference Attacks ICML 2021 Large-Capacity Image Steganography Based on Invertible Neural Networks CVPR 2021 Learner-Private Convex Optimization ICML 2021 Manipulating SGD with Data Ordering Attacks NeurIPS 2021 MAZE: Data-Free Model Stealing Attack Using Zeroth-Order Gradient Estimation CVPR 2021 Measuring data leakage in machine-learning models with Fisher information UAI 2021 Membership Inference Attacks Are Easier on Difficult Problems ICCV 2021 Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer EMNLP 2021 Modeling Deep Learning Based Privacy Attacks on Physical Mail AAAI 2021 (Nearly) Dimension Independent Private ERM with AdaGrad Rates\{via Publicly Estimated Subspaces COLT 2021 On InstaHide, Phase Retrieval, and Sparse Matrix Factorization ICLR 2021 On the Difficulty of Membership Inference Attacks CVPR 2021 On the Privacy Properties of GAN-generated Samples AISTATS 2021 Personalized and Invertible Face De-Identification by Disentangled Identity Information Manipulation ICCV 2021 Personalized Cross-Silo Federated Learning on Non-IID Data AAAI 2021 Practical and Private (Deep) Learning Without Sampling or Shuffling ICML 2021 Preventing Author Profiling through Zero-Shot Multilingual Back-Translation EMNLP 2021 Privacy enabled Financial Text Classification using Differential Privacy and Federated Learning EMNLP 2021 Privacy-Preserving Feature Extraction for Cloud-Based Wake Word Verification Interspeech 2021 Privacy-Preserving Image Features via Adversarial Affine Subspace Embeddings CVPR 2021 Privacy-Preserving Voice Anti-Spoofing Using Secure Multi-Party Computation Interspeech 2021 Protecting Intellectual Property of Generative Adversarial Networks From Ambiguity Attacks CVPR 2021