  The total variation distance is proposed as a privacy measure in an
information disclosure scenario when the goal is to reveal some information
about available data in return of utility, while retaining the privacy of
certain sensitive latent variables from the legitimate receiver. The total
variation distance is introduced as a measure of privacy-leakage by showing
that: i) it satisfies the post-processing and linkage inequalities, which makes
it consistent with an intuitive notion of a privacy measure; ii) the optimal
utility-privacy trade-off can be solved through a standard linear program when
total variation distance is employed as the privacy measure; iii) it provides a
bound on the privacy-leakage measured by mutual information, maximal leakage,
or the improvement in an inference attack with a bounded cost function.
