reconstruction attack

Enhanced Privacy Leakage from Noise-Perturbed Gradients via Gradient-Guided Conditional Diffusion Models AAAI 2026 Frequency-domain Manipulation for Face Obfuscation CVPR 2026 PrivSynth: Alternating and Control-Based Optimization for Privacy and Utility in Synthetic Data CVPR 2026 RAGFort: Dual-Path Defense Against Proprietary Knowledge Base Extraction in Retrieval-Augmented Generation AAAI 2026 Reconstruction Attack-Resistant Inference Paradigm for LLM Cloud Services AAAI 2026 Attribute Inference Attacks for Federated Regression Tasks AAAI 2025 LLMs are Privacy Erasable EMNLP 2025 On the Vulnerability of Text Sanitization NAACL 2025 PrivateEye: In-Sensor Privacy Preservation Through Optical Feature Separation WACV 2025 VVRec: Reconstruction Attacks on DL-based Volumetric Video Upstreaming via Latent Diffusion Model with Gamma Distribution AAAI 2025 Auditing Privacy Mechanisms via Label Inference Attacks NeurIPS 2024 PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning AAAI 2024 Privacy Attacks in Decentralized Learning ICML 2024 Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable NeurIPS 2024 Trained Random Forests Completely Reveal your Dataset ICML 2024 Bounding training data reconstruction in DP-SGD NeurIPS 2023 Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception? NeurIPS 2023 Privacy-Preserving Adversarial Facial Features CVPR 2023 Re-Thinking Model Inversion Attacks Against Deep Neural Networks CVPR 2023 TabLeak: Tabular Data Leakage in Federated Learning ICML 2023 Differentially Private Instance Encoding against Privacy Attacks NAACL 2022 Measuring Data Reconstruction Defenses in Collaborative Inference Systems NeurIPS 2022 Privacy-Preserving Collaborative Learning With Automatic Transformation Search CVPR 2021 Reconstruction Attack on Instance Encoding for Language Understanding EMNLP 2021 Differentially Private Small Dataset Release Using Random Projections UAI 2020