privacy attack

Data Poisoning Won’t Save You From Facial Recognition ICLR 2022 Deduplicating Training Data Mitigates Privacy Risks in Language Models ICML 2022 Differentially Private Instance Encoding against Privacy Attacks NAACL 2022 Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification ICML 2022 GradViT: Gradient Inversion of Vision Transformers CVPR 2022 Invernet: An Inversion Attack Framework to Infer Fine-Tuning Datasets through Word Embeddings EMNLP 2022 LAMP: Extracting Text from Gradients with Language Model Priors NeurIPS 2022 MExMI: Pool-based Active Model Extraction Crossover Membership Inference NeurIPS 2022 On the Importance of Difficulty Calibration in Membership Inference Attacks ICLR 2022 Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference NeurIPS 2022 Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks ICML 2022 Reconstructing Training Data From Diverse ML Models by Ensemble Inversion WACV 2022 Reconstructing Training Data From Trained Neural Networks NeurIPS 2022 Recovering Private Text in Federated Learning of Language Models NeurIPS 2022 RelaxLoss: Defending Membership Inference Attacks without Losing Utility ICLR 2022 Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models ICLR 2022 Exploiting Explanations for Model Inversion Attacks ICCV 2021 Gradient Inversion with Generative Image Prior NeurIPS 2021 GraphMI: Extracting Private Graph Data from Graph Neural Networks IJCAI 2021 How Does Data Augmentation Affect Privacy in Machine Learning? AAAI 2021 Knowledge-Enriched Distributional Model Inversion Attacks ICCV 2021 Label Inference Attacks from Log-loss Scores ICML 2021 Label-Only Membership Inference Attacks ICML 2021 Modeling Deep Learning Based Privacy Attacks on Physical Mail AAAI 2021 On the Difficulty of Membership Inference Attacks CVPR 2021