The paper proposes a multivariate all-pass filtering method and an m-LIP privacy measure for releasing multiple time series; the method preserves correlations, but the privacy guarantee has a serious inversion gap.
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Achieving Privacy Utility Balance for Multivariate Time Series Data
The paper proposes a multivariate all-pass filtering method and an m-LIP privacy measure for releasing multiple time series; the method preserves correlations, but the privacy guarantee has a serious inversion gap.