[HTML][HTML] DART: A Solution for decentralized federated learning model robustness analysis
Federated Learning (FL) has emerged as a promising approach to address privacy
concerns inherent in Machine Learning (ML) practices. However, conventional FL methods …
concerns inherent in Machine Learning (ML) practices. However, conventional FL methods …
On the Conflict of Robustness and Learning in Collaborative Machine Learning
M Raynal, C Troncoso - arXiv preprint arXiv:2402.13700, 2024 - arxiv.org
Collaborative Machine Learning (CML) allows participants to jointly train a machine learning
model while keeping their training data private. In scenarios where privacy is a strong …
model while keeping their training data private. In scenarios where privacy is a strong …
Creation of New Datasets for Decentralized Federated Learning
J Han, X Cheng, Z Zeng, H Ren - 2024 - zora.uzh.ch
The Internet of Things (IoT) is witnessing a rapid increase in the number of connected
devices, which are designed to process and communicate an enormous amount of data …
devices, which are designed to process and communicate an enormous amount of data …
Leveraging MTD to Mitigate Poisoning Attacks in Decentralized FL with Non-IID Data
C Feng, AH Celdrán, Z Zeng, Z Ye… - arXiv preprint arXiv …, 2024 - arxiv.org
Decentralized Federated Learning (DFL), a paradigm for managing big data in a privacy-
preserved manner, is still vulnerable to poisoning attacks where malicious clients tamper …
preserved manner, is still vulnerable to poisoning attacks where malicious clients tamper …
Mitigación de ataques bizantinos usando modelos históricos en aprendizaje federado descentralizado
ET Martínez Beltrán, PM Sánchez Sánchez… - … de Investigación en …, 2024 - idus.us.es
El Aprendizaje Federado Descentralizado emerge como una solución prometedora para
entrenar modelos de inteligencia artificial de manera colaborativa, sin compartir …
entrenar modelos de inteligencia artificial de manera colaborativa, sin compartir …
Securing Recommendation Systems in Federated Learning Based on Neural Collaborative Filtering Method with a Pairwise Approach
Recommendation systems are indispensable for delivering personalized recommendations
to users, yet the escalating concerns regarding data privacy have necessitated the …
to users, yet the escalating concerns regarding data privacy have necessitated the …