FSC-based data fusion sensitivity assessment scheme
Caiwen Wang, Rui Liu, Ke An · 2023
In recent years, with the large amount of data generated, data fusion and sharing have become more and more important. However, the expansion of the scope of data fusion and sharing has led to the increasing problem of data leakage risk. In this paper, we improve the FSC fusion algorithm to evaluate the sensitivity change during data fusion from three aspects: data set, data items and data values, so that the fused data sensitivity is more accurate, and later the fused data is anonymized for sharing. The algorithm reduces information loss and provides better privacy protection.