scholar.google.com › citations
Oct 21, 2023 · Our goal is to achieve PDP-FL without exposing clients' raw privacy budgets by indirectly partitioning the privacy preferences solely based on clients' noisy ...
Jul 9, 2024 · The meteoric rise of cross-silo Federated Learning (FL) is due to its ability to mitigate data breaches during collaborative training.
In this work, our goal is to achieve PDP-FL without exposing clients' raw privacy budgets by indirectly partitioning the privacy preferences solely based on ...
This work systematically investigates the unexplored question of under what conditions can the model updates of clients be primarily influenced by noise ...
By using the differential privacy technique, the proposed approach can reduce the impact of malicious agents without identifying them. Also, by adopting the ...
People also ask
What is the difference between federated learning and differential privacy?
What is the difference between federated learning and personalized federated learning?
What is privacy preserving federated learning?
What is private federated learning?
May 15, 2024 · We propose a new taxonomy of differentially private federated learning based on definition and guarantee of differential privacy and federated scenarios.
Aug 13, 2024 · This article introduces DP-LoRA, a novel federated learning algorithm tailored for LLMs. DP-LoRA preserves data privacy by employing a Gaussian mechanism.
In this paper, we propose PADP-FedMeta, a personalized and adaptive differentially private federated meta learning mechanism with a provable privacy and ...
Nov 5, 2024 · This paper, an improved Differential Privacy (DP) algorithm to protect the federated learning model. Additionally, the Fast Fourier Transform (FFT) is used.
This paper introduces a perturbation algorithm (PDPM) that satisfies personalized local differential privacy (PLDP), resolving the issue of inadequate or ...