Differential Privacy for Multiple Antenna Wireless Communication Assisted Federated Learning 


Vol. 49,  No. 2, pp. 308-311, Feb.  2024
10.7840/kics.2024.49.2.308


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  Abstract

In this work, we study differential privacy (DP) for federated learning over multiple antenna wireless communications. Specifically, we revisit DP from the perspective of wireless communications and propose an efficient beamforming scheme that can reduce inevitable degradation of inference accuracy due to intentional noises from DP. We also propose a power allocation scheme guaranteeing DP for the proposed beamforming scheme. Simulation results demonstrate that the proposed scheme can effectively prevent inference accuracy loss caused by DP.

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[IEEE Style]

J. Park and S. Yun, "Differential Privacy for Multiple Antenna Wireless Communication Assisted Federated Learning," The Journal of Korean Institute of Communications and Information Sciences, vol. 49, no. 2, pp. 308-311, 2024. DOI: 10.7840/kics.2024.49.2.308.

[ACM Style]

Junguk Park and Sangseok Yun. 2024. Differential Privacy for Multiple Antenna Wireless Communication Assisted Federated Learning. The Journal of Korean Institute of Communications and Information Sciences, 49, 2, (2024), 308-311. DOI: 10.7840/kics.2024.49.2.308.

[KICS Style]

Junguk Park and Sangseok Yun, "Differential Privacy for Multiple Antenna Wireless Communication Assisted Federated Learning," The Journal of Korean Institute of Communications and Information Sciences, vol. 49, no. 2, pp. 308-311, 2. 2024. (https://doi.org/10.7840/kics.2024.49.2.308)
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