3 papers
FLAegis: A Two-Layer Defense Framework for Federated Learning Against Poisoning Attacks
Enrique Mármol Campos, Aurora González Vidal, José Luis Hernández Ramos +1
Federated Learning (FL) has become a powerful technique for training Machine Learning (ML) models in a decentralized manner, preserving the privacy of the training datasets involve…
Federated Learning for Misbehaviour Detection with Variational Autoencoders and Gaussian Mixture Models
Enrique Mármol Campos, Aurora González Vidal, José Luis Hernández Ramos +1
Federated Learning (FL) has become an attractive approach to collaboratively train Machine Learning (ML) models while data sources' privacy is still preserved. However, most of exi…
Evaluating Federated Learning for Intrusion Detection in Internet of Things: Review and Challenges
Enrique Mármol Campos, Pablo Fernández Saura, Aurora González-Vidal +4
The application of Machine Learning (ML) techniques to the well-known intrusion detection systems (IDS) is key to cope with increasingly sophisticated cybersecurity attacks through…