DEFENDIS
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.
- Period
- Apr 2023 / Nov 2023
- Status
- Completed
- Institutional role
- Cybersecurity and Data Science Lab
- Partners
- CyberDataLab, armasuisse
- Outcome
- A defense-oriented approach to privacy-preserving IoT identification at the edge.
Decentralized Federated LearningAdversarial MLIoT Security+2
View Project
