Summary Statistic Privacy in Data Sharing. (arXiv:2303.02014v1 [cs.CR])

Data sharing between different parties has become increasingly common across
industry and academia. An important class of privacy concerns that arises in
data sharing scenarios regards the underlying distribution of data. For
example, the total traffic volume of data from a networking company can reveal
the scale of its business, which may be considered a trade secret.
Unfortunately, existing privacy frameworks (e.g., differential privacy,
anonymization) do not adequately address such concerns. In this paper, we
propose summary statistic privacy, a …

academia address business class data data sharing differential privacy distribution frameworks important industry may networking privacy scale secret sharing statistic trade traffic