:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Cho, Young Hyun, Sun, Will Wei
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Cryptography and Security
Online Access:	https://arxiv.org/abs/2410.22488
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

BACSA: A Bias-Aware Client Selection Algorithm for Privacy-Preserving Federated Learning in Wireless Healthcare Networks
by: Yadav, Sushilkumar, et al.
Published: (2024)

Privacy-Preserving in Blockchain-based Federated Learning Systems
by: M., Sameera K., et al.
Published: (2024)

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

Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks
by: Scheliga, Daniel, et al.
Published: (2023)

A Middle Path for On-Premises LLM Deployment: Preserving Privacy Without Sacrificing Model Confidentiality
by: Huang, Hanbo, et al.
Published: (2024)

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

Privacy-Preserving Federated Learning with Differentially Private Hyperdimensional Computing
by: Piran, Fardin Jalil, et al.
Published: (2024)

Privacy-Preserving Heterogeneous Federated Learning for Sensitive Healthcare Data
by: Xu, Yukai, et al.
Published: (2024)

Privacy-Preserving Federated Learning via Homomorphic Adversarial Networks
by: Dong, Wenhan, et al.
Published: (2024)

Effectiveness of L2 Regularization in Privacy-Preserving Machine Learning
by: Chandrinos, Nikolaos, et al.
Published: (2024)

Privacy-Preserving Intrusion Detection using Convolutional Neural Networks
by: Kodys, Martin, et al.
Published: (2024)

Optimizing Privacy-Preserving Primitives to Support LLM-Scale Applications
by: Jandali, Yaman, et al.
Published: (2025)

Learning Privacy-Preserving Student Networks via Discriminative-Generative Distillation
by: Ge, Shiming, et al.
Published: (2024)

CADRE: Customizable Assurance of Data Readiness in Privacy-Preserving Federated Learning
by: Hiniduma, Kaveen, et al.
Published: (2025)

Towards Privacy-Preserving Data-Driven Education: The Potential of Federated Learning
by: Khalil, Mohammad, et al.
Published: (2025)

Federated Inference: Toward Privacy-Preserving Collaborative and Incentivized Model Serving
by: Seo, Jungwon, et al.
Published: (2026)

ACU: Analytic Continual Unlearning for Efficient and Exact Forgetting with Privacy Preservation
by: Tang, Jianheng, et al.
Published: (2025)

Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models
by: Yu, Sixing, et al.
Published: (2023)

TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks
by: Maheri, Mohammad M, et al.
Published: (2025)

Generating Synthetic Health Sensor Data for Privacy-Preserving Wearable Stress Detection
by: Lange, Lucas, et al.
Published: (2024)

Efficient Privacy-Preserving Recommendation on Sparse Data using Fully Homomorphic Encryption
by: Chowdhury, Moontaha Nishat, et al.
Published: (2025)

Exploring the Privacy-Energy Consumption Tradeoff for Split Federated Learning
by: Lee, Joohyung, et al.
Published: (2023)

Privacy Preserving and Robust Aggregation for Cross-Silo Federated Learning in Non-IID Settings
by: Arazzi, Marco, et al.
Published: (2025)

MetaMoE: Diversity-Aware Proxy Selection for Privacy-Preserving Mixture-of-Experts Unification
by: Jiang, Weisen, et al.
Published: (2026)

Privacy-Preserving Data Sharing in Agriculture: Enforcing Policy Rules for Secure and Confidential Data Synthesis
by: Kotal, Anantaa, et al.
Published: (2023)

LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning Using a Lazy Influence Approximation
by: Rokvic, Ljubomir, et al.
Published: (2022)

A Survey of Privacy-Preserving Model Explanations: Privacy Risks, Attacks, and Countermeasures
by: Nguyen, Thanh Tam, et al.
Published: (2024)

PrivTune: Efficient and Privacy-Preserving Fine-Tuning of Large Language Models via Device-Cloud Collaboration
by: Liu, Yi, et al.
Published: (2025)

Feature-Aware Anisotropic Local Differential Privacy for Utility-Preserving Graph Representation Learning in Metal Additive Manufacturing
by: Islam, MD Shafikul, et al.
Published: (2026)

Towards Achieving Near-optimal Utility for Privacy-Preserving Federated Learning via Data Generation and Parameter Distortion
by: Zhang, Xiaojin, et al.
Published: (2023)

Bridging Privacy and Robustness for Trustworthy Machine Learning
by: Zhang, Xiaojin, et al.
Published: (2024)

Privacy Auditing of Multi-domain Graph Pre-trained Model under Membership Inference Attacks
by: Luo, Jiayi, et al.
Published: (2025)

Syntax- and Compilation-Preserving Evasion of LLM Vulnerability Detectors
by: Sun, Luze, et al.
Published: (2026)

PassREfinder-FL: Privacy-Preserving Credential Stuffing Risk Prediction via Graph-Based Federated Learning for Representing Password Reuse between Websites
by: Kim, Jaehan, et al.
Published: (2025)

Robust Privacy: Inference-Time Privacy through Certified Robustness
by: Jin, Jiankai, et al.
Published: (2026)

Towards Family-Grouped Hierarchical Federated Learning on Sub-5KB Models: A Feasibility Study of Privacy-Preserving ECG Monitoring for Ultra-Resource-Constrained Wearables
by: Wu, Hangyu
Published: (2026)

Beyond Data Privacy: New Privacy Risks for Large Language Models
by: Du, Yuntao, et al.
Published: (2025)

Your Privacy Depends on Others: Collusion Vulnerabilities in Individual Differential Privacy
by: Kaiser, Johannes, et al.
Published: (2026)