Differentially Private AirComp Federated Learning with Power Adaptation Harnessing Receiver Noise

14 Apr 2020Yusuke KodaKoji YamamotoTakayuki NishioMasahiro Morikura

Over-the-air computation (AirComp)-based federated learning (FL) enables low-latency uploads and the aggregation of machine learning models by exploiting simultaneous co-channel transmission and the resultant waveform superposition. This study aims at realizing secure AirComp-based FL against various privacy attacks where malicious central servers infer clients' private data from aggregated global models... (read more)

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