
DEFENDIS: Decentralized Federated Learning for IoT Device Identification and Security
DEFENDIS develops a framework for uniquely identifying IoT devices in a distributed manner while solving security threats through decentralized federated learning.
Research projects in federated learning, cybersecurity, resilient automation, and distributed systems for real-world environments.
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DEFENDIS develops a framework for uniquely identifying IoT devices in a distributed manner while solving security threats through decentralized federated learning.

A cutting-edge AI-based solution for automating cyber defence incident management processes, enhancing EU cyber defence posture and operational capabilities.

A modular, interoperable platform for coordinated emergency response in multi-victim disasters across European regions.

A comprehensive cybersecurity framework for Brain-Computer Interface systems in advanced driver assistance scenarios, focusing on detecting and preventing cyberattacks on the BCI lifecycle.