Copertina

Privacy-Enhanced Zero-Order Federated Learning via xMK-CKKS over Wireless Channels

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ayli, Anthony, Harris, Khalil, Fahs, Jihad, Assaad, Mohamad
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Cryptography and Security Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Collaborative Inference over Wireless Channels with Feature Differential Privacy
di: Seif, Mohamed, et al.
Pubblicazione: (2024)

Efficient Ranking, Order Statistics, and Sorting under CKKS
di: Mazzone, Federico, et al.
Pubblicazione: (2024)

Towards Privacy-Preserving Medical Imaging: Federated Learning with Differential Privacy and Secure Aggregation Using a Modified ResNet Architecture
di: Fares, Mohamad Haj, et al.
Pubblicazione: (2024)

Federated Low-Rank Adaptation with Differential Privacy over Wireless Networks
di: Kang, Tianqu, et al.
Pubblicazione: (2024)

Differential Privacy as a Perk: Federated Learning over Multiple-Access Fading Channels with a Multi-Antenna Base Station
di: Liang, Hao, et al.
Pubblicazione: (2025)

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

Blockchain-Enabled Privacy-Preserving Second-Order Federated Edge Learning in Personalized Healthcare
di: Nawaz, Anum, et al.
Pubblicazione: (2025)

Comments on "Privacy-Enhanced Federated Learning Against Poisoning Adversaries"
di: Schneider, Thomas, et al.
Pubblicazione: (2024)

Starlit: Privacy-Preserving Federated Learning to Enhance Financial Fraud Detection
di: Abadi, Aydin, et al.
Pubblicazione: (2024)

Scaling up Privacy-Preserving ML: A CKKS Implementation of Llama-2-7B
di: Park, Jaiyoung, et al.
Pubblicazione: (2026)

FLARE: A Wireless Side-Channel Fingerprinting Attack on Federated Learning
di: Shuvo, Md Nahid Hasan, et al.
Pubblicazione: (2025)

A Novel Federated Learning-Based IDS for Enhancing UAVs Privacy and Security
di: Ceviz, Ozlem, et al.
Pubblicazione: (2023)

Privacy Side Channels in Machine Learning Systems
di: Debenedetti, Edoardo, et al.
Pubblicazione: (2023)

DDP-SA: Scalable Privacy-Preserving Federated Learning via Distributed Differential Privacy and Secure Aggregation
di: Wei, Wenjing, et al.
Pubblicazione: (2026)

On the Efficiency of Privacy Attacks in Federated Learning
di: Tabassum, Nawrin, et al.
Pubblicazione: (2024)

Preserving Privacy and Security in Federated Learning
di: Nguyen, Truc, et al.
Pubblicazione: (2022)

Adversary-Aware Private Inference over Wireless Channels
di: Seif, Mohamed, et al.
Pubblicazione: (2025)

FHE-Agent: Automating CKKS Configuration for Practical Encrypted Inference via an LLM-Guided Agentic Framework
di: Xu, Nuo, et al.
Pubblicazione: (2025)

Deep Learning under Fractional-Order Differential Privacy
di: Partohaghighi, Mohammad, et al.
Pubblicazione: (2026)

Survey of Privacy Threats and Countermeasures in Federated Learning
di: Hayashitani, Masahiro, et al.
Pubblicazione: (2024)

FinP: Fairness-in-Privacy in Federated Learning by Addressing Disparities in Privacy Risk
di: Zhao, Tianyu, et al.
Pubblicazione: (2025)

Efficient Mod Approximation and Its Applications to CKKS Ciphertexts
di: Zhou, Yufei
Pubblicazione: (2025)

Turning Federated Learning Systems Into Covert Channels
di: Costa, Gabriele, et al.
Pubblicazione: (2021)

Convergent Differential Privacy Analysis for General Federated Learning
di: Sun, Yan, et al.
Pubblicazione: (2024)

One-shot Empirical Privacy Estimation for Federated Learning
di: Andrew, Galen, et al.
Pubblicazione: (2023)

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy
di: Li, Xiang, et al.
Pubblicazione: (2025)

Enhancing Privacy in ControlNet and Stable Diffusion via Split Learning
di: Yao, Dixi
Pubblicazione: (2024)

Immersion and Invariance-based Coding for Privacy-Preserving Federated Learning
di: Hayati, Haleh, et al.
Pubblicazione: (2024)

Towards Explainable Federated Learning: Understanding the Impact of Differential Privacy
di: Oliveira, Júlio, et al.
Pubblicazione: (2026)

FedRE: Robust and Effective Federated Learning with Privacy Preference
di: Xiao, Tianzhe, et al.
Pubblicazione: (2025)

Complex-valued Federated Learning with Differential Privacy and MRI Applications
di: Riess, Anneliese, et al.
Pubblicazione: (2021)

Social-Aware Clustered Federated Learning with Customized Privacy Preservation
di: Wang, Yuntao, et al.
Pubblicazione: (2022)

DeMem: Privacy-Enhanced Robust Adversarial Learning via De-Memorization
di: Luo, Xiaoyu, et al.
Pubblicazione: (2024)

Triple-Hoisted Baby-Step Giant-Step Linear Transformation over CKKS Homomorphic Encryption and Hardware Accelerator
di: Akherati, Sajjad, et al.
Pubblicazione: (2026)

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning
di: Zeng, Zhihao, et al.
Pubblicazione: (2025)

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

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

Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM
di: Xie, Chulin, et al.
Pubblicazione: (2022)

On Evaluating the Poisoning Robustness of Federated Learning under Local Differential Privacy
di: Wang, Zijian, et al.
Pubblicazione: (2025)

Privacy-Preserving Edge Federated Learning for Intelligent Mobile-Health Systems
di: Aminifar, Amin, et al.
Pubblicazione: (2024)