E-MagDiP: Electro-Magnetic based Differential Privacy for EEG based Community Sensing

[Paper]

Ayanga Kalupahana, Vishruti Ranjan and Li-Shiuan Peh
National University of Singapore, Singapore

Abstract

EEG-based community sensing programs raise privacy concerns because EEG signals contain sensitive personal information. Differential Privacy (DP) can protect individuals while preserving aggregate statistics, yet applying DP to EEG data is challenging: it requires user-level noise generation, which increases power and latency; Besides, most commercial EEG headsets cannot be modified to add such noise. We propose E-MagDiP, a framework that uses an external radio to transmit RF signals onto EEG headsets, perturbing at acquisition to induce DP noise. Experiments on three off-the-shelf headsets show E-MagDiP’s ability of providing DP guarantee 38.12 for 100 participants. E-MagDiP is the first framework to use RF signals for privacy instead of attacks, enabling practical DP for EEG community sensing without any user-level modification.

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