Add to ORKGThe Federated Learning method was developed to to provide an alternative for the recent concerns with data privacy in machine learning. This method involves multiple parties to privately train local machine learning models with their own data, sharing with the global server only the models’ parameters that will be averaged to update the global model. Although private, such environments are constantly at the risk of suffering cyber-attacks that can compromise the information used in the process and/or the complete machine learning training. This work investigates the application of Digital Envelopes combined with Federated Learning, to improve protection against attacks to either the clients and the server.publishe
Federated learning is a privacy-aware collaborative machine learning method where the clients collab...
As data are increasingly being stored in different silos and societies becoming more aware of data p...
Abstract Federated learning is a privacy-aware collaborative machine learning method, but it needs o...
Recent concerns with data privacy in machine learning have led to the development of privacypreservi...
Federated learning is an improved version of distributed machine learning that further offloads oper...
AI\u27s applicability across diverse fields is hindered by data sensitivity, privacy concerns, and l...
Federated learning (FL), a variant of distributed learning (DL), supports the training of a shared m...
With the rise of artificial intelligence, the need for data also increases. However, many strict da...
One of the new trends in the field of artificial intelligence is federated learning (FL), which will...
Machine learning models benefit from large and diverse training datasets. However, it is difficult f...
A possible approach to address the increasing security and privacy concerns is federated learning (F...
Federated learning is a machine learning paradigm that emerges as a solution to the privacy-preserva...
Federated learning is a machine learning paradigm that emerges as a solution to the privacy-preserv...
Federated learning (FL) enables multiple clients to jointly train a global learning model while keep...
There is a potential in the field of medicine and finance of doing collaborative machine learning. T...
Federated learning is a privacy-aware collaborative machine learning method where the clients collab...
As data are increasingly being stored in different silos and societies becoming more aware of data p...
Abstract Federated learning is a privacy-aware collaborative machine learning method, but it needs o...
Recent concerns with data privacy in machine learning have led to the development of privacypreservi...
Federated learning is an improved version of distributed machine learning that further offloads oper...
AI\u27s applicability across diverse fields is hindered by data sensitivity, privacy concerns, and l...
Federated learning (FL), a variant of distributed learning (DL), supports the training of a shared m...
With the rise of artificial intelligence, the need for data also increases. However, many strict da...
One of the new trends in the field of artificial intelligence is federated learning (FL), which will...
Machine learning models benefit from large and diverse training datasets. However, it is difficult f...
A possible approach to address the increasing security and privacy concerns is federated learning (F...
Federated learning is a machine learning paradigm that emerges as a solution to the privacy-preserva...
Federated learning is a machine learning paradigm that emerges as a solution to the privacy-preserv...
Federated learning (FL) enables multiple clients to jointly train a global learning model while keep...
There is a potential in the field of medicine and finance of doing collaborative machine learning. T...
Federated learning is a privacy-aware collaborative machine learning method where the clients collab...
As data are increasingly being stored in different silos and societies becoming more aware of data p...
Abstract Federated learning is a privacy-aware collaborative machine learning method, but it needs o...