conftrace_

privacy leakage

105 papers

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Co-occurring keywords

large language model (13587) membership inference (114) federated learning (1333) differential privacy (1016) adversarial attack (1621) language model (4599) membership inference attack (93) privacy preservation (380) privacy attack (119) personally identifiable information (33)

Papers

On the Privacy Risks of Algorithmic Recourse AISTATS 2023
Bag of Tricks for Training Data Extraction from Language Models ICML 2023
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models ICML 2023
TabLeak: Tabular Data Leakage in Federated Learning ICML 2023
Privacy-Aware Rejection Sampling JMLR 2023
On the Universal Adversarial Perturbations for Efficient Data-free Adversarial Detection ACL 2023
GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization ICCV 2023
Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception? NIPS 2023
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning AAAI 2023
Anonymization for Skeleton Action Recognition AAAI 2023
Amplifying Membership Exposure via Data Poisoning NIPS 2022
Membership Inference Attacks Against Self-supervised Speech Models INTERSPEECH 2022
Privacy Leakage in Text Classification A Data Extraction Approach NAACL 2022
You Don’t Know My Favorite Color: Preventing Dialogue Representations from Revealing Speakers’ Private Personas NAACL 2022
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification ICML 2022
Extracting Targeted Training Data from ASR Models, and How to Mitigate It INTERSPEECH 2022
In Differential Privacy, There is Truth: on Vote-Histogram Leakage in Ensemble Private Learning NIPS 2022
User-Level Differential Privacy against Attribute Inference Attack of Speech Emotion Recognition on Federated Learning INTERSPEECH 2022
Leveraging Adversarial Examples To Quantify Membership Information Leakage CVPR 2022
Extracted BERT Model Leaks More Information than You Think! EMNLP 2022
Are Large Pre-Trained Language Models Leaking Your Personal Information? EMNLP 2022
M$^4$I: Multi-modal Models Membership Inference NIPS 2022
Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models AISTATS 2021
TAG: Gradient Attack on Transformer-based Language Models EMNLP 2021
Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent NIPS 2021