Abstract:For models trained on-premise but deployed in a distributed fashion across multiple entities, we demonstrate that minimizing distance correlation between sensitive data such as faces and intermediary representations enables prediction while preventing reconstruction attacks. Leakage (measured using distance correlation between input and intermediate representations) is the risk associated with the reconstruction of raw face data from intermediary representations that are communicated in a distributed setting. … Show more
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