Cover Image

Generating Privacy-Preserving Personalized Advice with Zero-Knowledge Proofs and LLMs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Watanabe, Hiroki, Uchikoshi, Motonobu
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Privacy-Preserving LLMs Routing
by: Wu, Xidong, et al.
Published: (2026)

Zero-Knowledge Proofs in Sublinear Space
by: Nye, Logan
Published: (2025)

NOIR: Privacy-Preserving Generation of Code with Open-Source LLMs
by: Nguyen, Khoa, et al.
Published: (2026)

Zero-Knowledge Audit for Internet of Agents: Privacy-Preserving Communication Verification with Model Context Protocol
by: Jing, Guanlin, et al.
Published: (2025)

Zero-Knowledge Federated Learning: A New Trustworthy and Privacy-Preserving Distributed Learning Paradigm
by: Wang, Taotao, et al.
Published: (2025)

KnowledgeSG: Privacy-Preserving Synthetic Text Generation with Knowledge Distillation from Server
by: Wang, Wenhao, et al.
Published: (2024)

ZK-APEX: Zero-Knowledge Approximate Personalized Unlearning with Executable Proofs
by: Maheri, Mohammad M, et al.
Published: (2025)

Zero-Knowledge Proof Based Verifiable Inference of Models
by: Wang, Yunxiao
Published: (2025)

Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation
by: Ma, Qian, et al.
Published: (2026)

Privacy Preserving Machine Learning Workflow: from Anonymization to Personalized Differential Privacy Budgets in Federated Learning
by: Díaz, Judith Sáinz-Pardo, et al.
Published: (2026)

Efficient Privacy-Preserving Retrieval Augmented Generation with Distance-Preserving Encryption
by: Ye, Huanyi, et al.
Published: (2026)

KIPPS: Knowledge infusion in Privacy Preserving Synthetic Data Generation
by: Kotal, Anantaa, et al.
Published: (2024)

Towards Privacy-Preserving and Personalized Smart Homes via Tailored Small Language Models
by: Huang, Xinyu, et al.
Published: (2025)

ZORRO: Zero-Knowledge Robustness and Privacy for Split Learning (Full Version)
by: Sheybani, Nojan, et al.
Published: (2025)

VeriLoRA: Fine-Tuning Large Language Models with Verifiable Security via Zero-Knowledge Proofs
by: Liao, Guofu, et al.
Published: (2025)

Kick Bad Guys Out! Conditionally Activated Anomaly Detection in Federated Learning with Zero-Knowledge Proof Verification
by: Han, Shanshan, et al.
Published: (2023)

Ensemble Privacy Defense for Knowledge-Intensive LLMs against Membership Inference Attacks
by: Fu, Haowei, et al.
Published: (2025)

RL-Finetuned LLMs for Privacy-Preserving Synthetic Rewriting
by: Shi, Zhan, et al.
Published: (2025)

GOD model: Privacy Preserved AI School for Personal Assistant
by: PIN AI Team, et al.
Published: (2025)

Privacy Preservation in Gen AI Applications
by: S, Swetha, et al.
Published: (2025)

Privacy-Preserving Retrieval-Augmented Generation with Differential Privacy
by: Koga, Tatsuki, et al.
Published: (2024)

PRIVATEEDIT: A Privacy-Preserving Pipeline for Face-Centric Generative Image Editing
by: Tamboli, Dipesh, et al.
Published: (2026)

SPDZCoder: Combining Expert Knowledge with LLMs for Generating Privacy-Computing Code
by: Dong, Xiaoning, et al.
Published: (2024)

PrivacyRestore: Privacy-Preserving Inference in Large Language Models via Privacy Removal and Restoration
by: Zeng, Ziqian, et al.
Published: (2024)

ZKLoRA: Efficient Zero-Knowledge Proofs for LoRA Verification
by: Roy, Bidhan, et al.
Published: (2025)

A Survey of Zero-Knowledge Proof Based Verifiable Machine Learning
by: Peng, Zhizhi, et al.
Published: (2025)

Privacy-Preserving Decentralized AI with Confidential Computing
by: Lee, Dayeol, et al.
Published: (2024)

Privacy-Preserving Decentralized Federated Learning via Explainable Adaptive Differential Privacy
by: Piran, Fardin Jalil, et al.
Published: (2025)

On the Privacy of LLMs: An Ablation Study
by: Makhlouf, Karima, et al.
Published: (2026)

NANOZK: Layerwise Zero-Knowledge Proofs for Verifiable Large Language Model Inference
by: Wang, Zhaohui Geoffrey
Published: (2026)

zkFL: Zero-Knowledge Proof-based Gradient Aggregation for Federated Learning
by: Wang, Zhipeng, et al.
Published: (2023)

Privacy-Preserving, Dropout-Resilient Aggregation in Decentralized Learning
by: Ghavamipour, Ali Reza, et al.
Published: (2024)

No Free Lunch Theorem for Privacy-Preserving LLM Inference
by: Zhang, Xiaojin, et al.
Published: (2024)

Privacy-Preserving Diffusion Model Using Homomorphic Encryption
by: Chen, Yaojian, et al.
Published: (2024)

Privacy-Preserving Aggregation for Decentralized Learning with Byzantine-Robustness
by: Ghavamipour, Ali Reza, et al.
Published: (2024)

Scaling While Privacy Preserving: A Comprehensive Synthetic Tabular Data Generation and Evaluation in Learning Analytics
by: Liu, Qinyi, et al.
Published: (2024)

TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning
by: Xu, Runhua, et al.
Published: (2025)

A Quantization-based Technique for Privacy Preserving Distributed Learning
by: Colombo, Maurizio, et al.
Published: (2024)

Towards Trustworthy AI: Secure Deepfake Detection using CNNs and Zero-Knowledge Proofs
by: Islam, H M Mohaimanul, et al.
Published: (2025)

Data-Free Privacy-Preserving for LLMs via Model Inversion and Selective Unlearning
by: Zhou, Xinjie, et al.
Published: (2026)