Security & Privacy

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 PAPRIKA: Private Online False Discovery Rate Control ICML 2021 PATE-AAE: Incorporating Adversarial Autoencoder into Private Aggregation of Teacher Ensembles for Spoken Command Classification Interspeech 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 Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates ICML 2021 Privately Publishable Per-instance Privacy NeurIPS 2021 Private Release of Text Embedding Vectors NAACL 2021 Protecting Intellectual Property of Generative Adversarial Networks From Ambiguity Attacks CVPR 2021 Reconstruction Attack on Instance Encoding for Language Understanding EMNLP 2021 Rethinking the Backdoor Attacks' Triggers: A Frequency Perspective ICCV 2021 Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing ICML 2021 SecDD: Efficient and Secure Method for Remotely Training Neural Networks (Student Abstract) AAAI 2021 Secure Deep Graph Generation with Link Differential Privacy IJCAI 2021 See Through Gradients: Image Batch Recovery via GradInversion CVPR 2021 Single and Multiple Change-Point Detection with Differential Privacy JMLR 2021 Soteria: Provable Defense Against Privacy Leakage in Federated Learning From Representation Perspective CVPR 2021