PrivacyRestore: Privacy-Preserving Inference in Large Language Models via Privacy Removal and Restoration
Fuente:
arXiv
Saved in:
| Main Authors: | Zeng, Ziqian, Wang, Jianwei, Yang, Junyao, Lu, Zhengdong, Li, Haoran, Zhuang, Huiping, Chen, Cen |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
RewardDS: Privacy-Preserving Fine-Tuning for Large Language Models via Reward Driven Data Synthesis
by: Wang, Jianwei, et al.
Published: (2025)
by: Wang, Jianwei, et al.
Published: (2025)
SEA: Low-Resource Safety Alignment for Multimodal Large Language Models via Synthetic Embeddings
by: Lu, Weikai, et al.
Published: (2025)
by: Lu, Weikai, et al.
Published: (2025)
Privacy-Preserving Decentralized Federated Learning via Explainable Adaptive Differential Privacy
by: Piran, Fardin Jalil, et al.
Published: (2025)
by: Piran, Fardin Jalil, et al.
Published: (2025)
No Free Lunch Theorem for Privacy-Preserving LLM Inference
by: Zhang, Xiaojin, et al.
Published: (2024)
by: Zhang, Xiaojin, et al.
Published: (2024)
Towards Privacy-Preserving Large Language Model: Text-free Inference Through Alignment and Adaptation
by: Yoon, Jeongho, et al.
Published: (2026)
by: Yoon, Jeongho, et al.
Published: (2026)
User Behavior Analysis in Privacy Protection with Large Language Models: A Study on Privacy Preferences with Limited Data
by: Yang, Haowei, et al.
Published: (2025)
by: Yang, Haowei, et al.
Published: (2025)
Privacy-Preserving Large Language Models: Mechanisms, Applications, and Future Directions
by: Zhao, Guoshenghui, et al.
Published: (2024)
by: Zhao, Guoshenghui, et al.
Published: (2024)
InferDPT: Privacy-Preserving Inference for Closed-box Large Language Model
by: Tong, Meng, et al.
Published: (2023)
by: Tong, Meng, et al.
Published: (2023)
Towards Privacy-Preserving LLM Inference via Covariant Obfuscation (Technical Report)
by: Lin, Yu, et al.
Published: (2026)
by: Lin, Yu, et al.
Published: (2026)
Privacy-Preserving Diffusion Model Using Homomorphic Encryption
by: Chen, Yaojian, et al.
Published: (2024)
by: Chen, Yaojian, et al.
Published: (2024)
Privacy-Preserving LLMs Routing
by: Wu, Xidong, et al.
Published: (2026)
by: Wu, Xidong, et al.
Published: (2026)
SoK: Semantic Privacy in Large Language Models
by: Ma, Baihe, et al.
Published: (2025)
by: Ma, Baihe, et al.
Published: (2025)
Towards Privacy-Preserving and Personalized Smart Homes via Tailored Small Language Models
by: Huang, Xinyu, et al.
Published: (2025)
by: Huang, Xinyu, et al.
Published: (2025)
Beyond Data Privacy: New Privacy Risks for Large Language Models
by: Du, Yuntao, et al.
Published: (2025)
by: Du, Yuntao, et al.
Published: (2025)
ACU: Analytic Continual Unlearning for Efficient and Exact Forgetting with Privacy Preservation
by: Tang, Jianheng, et al.
Published: (2025)
by: Tang, Jianheng, et al.
Published: (2025)
Privacy-Preserving ECG Data Analysis with Differential Privacy: A Literature Review and A Case Study
by: Ghazarian, Arin, et al.
Published: (2024)
by: Ghazarian, Arin, et al.
Published: (2024)
Privacy-Preserving Retrieval-Augmented Generation with Differential Privacy
by: Koga, Tatsuki, et al.
Published: (2024)
by: Koga, Tatsuki, et al.
Published: (2024)
Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss
by: Liu, Zhenlong, et al.
Published: (2024)
by: Liu, Zhenlong, et al.
Published: (2024)
Privacy Preservation in Gen AI Applications
by: S, Swetha, et al.
Published: (2025)
by: S, Swetha, et al.
Published: (2025)
Privacy-Preserving Inference for Quantized BERT Models
by: Lu, Tianpei, et al.
Published: (2025)
by: Lu, Tianpei, et al.
Published: (2025)
User Privacy and Large Language Models: An Analysis of Frontier Developers' Privacy Policies
by: King, Jennifer, et al.
Published: (2025)
by: King, Jennifer, et al.
Published: (2025)
Federated Inference: Toward Privacy-Preserving Collaborative and Incentivized Model Serving
by: Seo, Jungwon, et al.
Published: (2026)
by: Seo, Jungwon, et al.
Published: (2026)
Privacy Auditing of Large Language Models
by: Panda, Ashwinee, et al.
Published: (2025)
by: Panda, Ashwinee, et al.
Published: (2025)
Privacy-Preserving Federated Unlearning with Certified Client Removal
by: Liu, Ziyao, et al.
Published: (2024)
by: Liu, Ziyao, et al.
Published: (2024)
FedRW: Efficient Privacy-Preserving Data Reweighting for Enhancing Federated Learning of Language Models
by: Ye, Pukang, et al.
Published: (2025)
by: Ye, Pukang, et al.
Published: (2025)
PrivacyGo: Privacy-Preserving Ad Measurement with Multidimensional Intersection
by: Du, Jian, et al.
Published: (2025)
by: Du, Jian, et al.
Published: (2025)
PrivacyLens: Evaluating Privacy Norm Awareness of Language Models in Action
by: Shao, Yijia, et al.
Published: (2024)
by: Shao, Yijia, et al.
Published: (2024)
A Survey: Towards Privacy and Security in Mobile Large Language Models
by: Xu, Honghui, et al.
Published: (2025)
by: Xu, Honghui, et al.
Published: (2025)
Data-Free Privacy-Preserving for LLMs via Model Inversion and Selective Unlearning
by: Zhou, Xinjie, et al.
Published: (2026)
by: Zhou, Xinjie, et al.
Published: (2026)
Privacy-Preserving Decentralized AI with Confidential Computing
by: Lee, Dayeol, et al.
Published: (2024)
by: Lee, Dayeol, et al.
Published: (2024)
ARGUS: Defending Against Multimodal Indirect Prompt Injection via Steering Instruction-Following Behavior
by: Lu, Weikai, et al.
Published: (2025)
by: Lu, Weikai, et al.
Published: (2025)
LLM-PBE: Assessing Data Privacy in Large Language Models
by: Li, Qinbin, et al.
Published: (2024)
by: Li, Qinbin, et al.
Published: (2024)
Privacy Preserving Machine Learning Workflow: from Anonymization to Personalized Differential Privacy Budgets in Federated Learning
by: Díaz, Judith Sáinz-Pardo, et al.
Published: (2026)
by: Díaz, Judith Sáinz-Pardo, et al.
Published: (2026)
Design and Optimization of Cloud Native Homomorphic Encryption Workflows for Privacy-Preserving ML Inference
by: Bollikonda, Tejaswini
Published: (2025)
by: Bollikonda, Tejaswini
Published: (2025)
EP-HDC: Hyperdimensional Computing with Encrypted Parameters for High-Throughput Privacy-Preserving Inference
by: Park, Jaewoo, et al.
Published: (2025)
by: Park, Jaewoo, et al.
Published: (2025)
Robust Privacy: Inference-Time Privacy through Certified Robustness
by: Jin, Jiankai, et al.
Published: (2026)
by: Jin, Jiankai, et al.
Published: (2026)
PrivacyXray: Detecting Privacy Breaches in LLMs through Semantic Consistency and Probability Certainty
by: He, Jinwen, et al.
Published: (2025)
by: He, Jinwen, et al.
Published: (2025)
Learning Privacy-Preserving Student Networks via Discriminative-Generative Distillation
by: Ge, Shiming, et al.
Published: (2024)
by: Ge, Shiming, et al.
Published: (2024)
Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models
by: Yu, Sixing, et al.
Published: (2023)
by: Yu, Sixing, et al.
Published: (2023)
Deciphering the Interplay between Attack and Protection Complexity in Privacy-Preserving Federated Learning
by: Zhang, Xiaojin, et al.
Published: (2025)
by: Zhang, Xiaojin, et al.
Published: (2025)
Similar Items
-
RewardDS: Privacy-Preserving Fine-Tuning for Large Language Models via Reward Driven Data Synthesis
by: Wang, Jianwei, et al.
Published: (2025) -
SEA: Low-Resource Safety Alignment for Multimodal Large Language Models via Synthetic Embeddings
by: Lu, Weikai, et al.
Published: (2025) -
Privacy-Preserving Decentralized Federated Learning via Explainable Adaptive Differential Privacy
by: Piran, Fardin Jalil, et al.
Published: (2025) -
No Free Lunch Theorem for Privacy-Preserving LLM Inference
by: Zhang, Xiaojin, et al.
Published: (2024) -
Towards Privacy-Preserving Large Language Model: Text-free Inference Through Alignment and Adaptation
by: Yoon, Jeongho, et al.
Published: (2026)