Enhanced Security and Privacy for Wireless Federated Learning (SP4WFL)
Research Project, 2020
– 2021
The main goal of this research is to come up with efficient solutions to mitigate security and privacy threats in wireless federated learning. We aim to develop solutions in the physical layer of the wireless communication system that can provide improvements in security and privacy. Inspired by ideas in the physical layer security literature, we aim to investigate whether the inherent randomness due to channel fluctuations, distortions, and noise introduced by the transceiver hardware can be exploited with carefully designed transmission schemes/protocols to make federated learning robust to privacy and security threats.
Participants
Sina Rezaei Aghdam (contact)
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Marija Furdek Prekratic
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Alexandre Graell I Amat
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Funding
Chalmers AI Research Centre (CHAIR)
Project ID: 2020-013 CHAIR CO
Funding Chalmers participation during 2020–2021
Related Areas of Advance and Infrastructure
Information and Communication Technology
Areas of Advance