Sentinel: An Aggregation Function to Secure Decentralized Federated Learning

no code implementations • 12 Oct 2023 • Chao Feng, Alberto Huertas Celdran, Janosch Baltensperger, Enrique Tomas Martinez Beltran, Gerome Bovet, Burkhard Stiller

The rapid integration of Federated Learning (FL) into networking encompasses various aspects such as network management, quality of service, and cybersecurity while preserving data privacy.

Federated Learning Management

CyberForce: A Federated Reinforcement Learning Framework for Malware Mitigation

no code implementations • 11 Aug 2023 • Chao Feng, Alberto Huertas Celdran, Pedro Miguel Sanchez Sanchez, Jan Kreischer, Jan von der Assen, Gerome Bovet, Gregorio Martinez Perez, Burkhard Stiller

Recent research has shown that the integration of Reinforcement Learning (RL) with Moving Target Defense (MTD) can enhance cybersecurity in Internet-of-Things (IoT) devices.

Anomaly Detection Data Poisoning +3

FedDICE: A ransomware spread detection in a distributed integrated clinical environment using federated learning and SDN based mitigation

no code implementations • 9 Jun 2021 • Chandra Thapa, Kallol Krishna Karmakar, Alberto Huertas Celdran, Seyit Camtepe, Vijay Varadharajan, Surya Nepal

FedDICE integrates federated learning (FL), which is privacy-preserving learning, to SDN-oriented security architecture to enable collaborative learning, detection, and mitigation of ransomware attacks.

Federated Learning Privacy Preserving