Experimentally Validated Quantum-Secure Federated Learning over a Multi-user Quantum Network. [PDF]
Research (Wash D C)Liu ZP +8 more
europepmc +1 more source
RepFed-Net: privacy-preserving federated learning with reputation-aware aggregation for retinal vessel segmentation using enhanced U-Net. [PDF]
Sci RepSri AV, Morampudi MK.
europepmc +1 more source
A blockchain technology with advanced lightweight symmetric cryptography schemes and smart security framework for healthcare wireless body area networks. [PDF]
Sci RepMuthupandian S, Kumar DM.
europepmc +1 more source
A federated learning framework for deep imputation of missing data in heterogeneous ICU time series. [PDF]
Sci RepVavekanand R, Sathio AA, Sultani M.
europepmc +1 more source
FedSMOTE-DP: Privacy-Aware Federated Ensemble Learning for Intrusion Detection in IoMT Networks. [PDF]
Sensors (Basel)Alsolami T, Ilyas M.
europepmc +1 more source
Federated Gastrointestinal Lesion Classification with Clinical-Entropy Guided Quantum-Inspired Token Pruning in Vision Transformers. [PDF]
Diagnostics (Basel)Awais M, Qamar AM, Khalid U, Khan RU.
europepmc +1 more source
Related searches:
Pain-FL: Personalized Privacy-Preserving Incentive for Federated Learning
IEEE Journal on Selected Areas in Communications, 2021Federated learning (FL) is a privacy-preserving distributed machine learning framework, which involves training statistical models over a number of mobile users (i.e., workers) while keeping data localized. However, recent works have demonstrated that workers engaged in FL are still susceptible to advanced inference attacks when sharing model updates ...
Peng Sun 0003 +6 more
openaire +1 more source
FL-HDC: Hyperdimensional Computing Design for the Application of Federated Learning
2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2021Federated learning (FL) is a privacy-preserving learning framework, which collaboratively learns a centralized model across edge devices. Each device trains an independent model with its local dataset and only uploads model parameters to mitigate privacy concerns.
Cheng-Yen Hsieh +2 more
openaire +1 more source
Chain FL: Decentralized Federated Machine Learning via Blockchain
2020 Second International Conference on Blockchain Computing and Applications (BCCA), 2020Federated learning is a collaborative machine learning mechanism that allows multiple parties to develop a model without sharing the training data. It is a promising mechanism since it empowers collaboration in fields such as medicine and banking where data sharing is not favorable due to legal, technical, ethical, or safety issues without ...
Caner Korkmaz +5 more
openaire +1 more source
Federated Learning (FL) – Overview
LETI Transactions on Electrical Engineering & Computer ScienceExplores the fundamental aspects of federated learning (FL) in the context of intrusion detection systems (IDS) within Internet of Things (IoT) networks. Federated learning presents an innovative approach to training machine learning models on distributed devices, thereby minimizing the need to transmit sensitive data to central servers. We classify FL
M. Al-Tameemi, M. B. Hassan, S. A. Abass
openaire +1 more source