Survey on federated learning for intrusion detection system: Concept, architectures, aggregation strategies, challenges, and future directions
Intrusion Detection Systems (IDS) are essential for securing computer networks by
identifying and mitigating potential threats. However, traditional IDS face challenges related …
identifying and mitigating potential threats. However, traditional IDS face challenges related …
How to prevent the poor performance clients for personalized federated learning?
Personalized federated learning (pFL) collaboratively trains personalized models, which
provides a customized model solution for individual clients in the presence of …
provides a customized model solution for individual clients in the presence of …
Text-driven prompt generation for vision-language models in federated learning
C Qiu, X Li, CK Mummadi, MR Ganesh, Z Li… - ar** a reliable energy forecasting model requires a large-scale …
FedGCA: Global Consistent Augmentation Based Single-Source Federated Domain Generalization
Federated Domain Generalization (FedDG) aims to train the global model for generalization
ability to unseen domains with multi-domain training samples. However, clients in federated …
ability to unseen domains with multi-domain training samples. However, clients in federated …
Controlled privacy leakage propagation throughout overlap** grouped learning
Federated Learning (FL) is the standard protocol for collaborative learning. In FL, multiple
workers jointly train a shared model. They exchange model updates calculated on their data …
workers jointly train a shared model. They exchange model updates calculated on their data …
Spyker: Asynchronous Multi-Server Federated Learning for Geo-Distributed Clients
Federated learning (FL) systems enable multiple clients to train a machine learning model
iteratively through synchronously exchanging the intermediate model weights with a single …
iteratively through synchronously exchanging the intermediate model weights with a single …
Leader Selection and Follower Association for UE-centric Distributed Learning in Future Wireless Networks
S Parsaeefard, S Roessel, AG Ghavamabad… - IEEE …, 2024 - ieeexplore.ieee.org
This paper focuses on UE-centric DL algorithms where UEs initiate requests to adapt AI/ML
models for better performance in dynamic environment, eg, locally refined AI/ML models …
models for better performance in dynamic environment, eg, locally refined AI/ML models …