This explainer document aims to provide an overview of the current state of the rapidly
expanding work on synthetic data technologies, with a particular focus on privacy. The …

Given two random variables X and Y, an operational approach is undertaken to quantify the
“leakage” of information from X to Y. The resulting measure L (X→ Y) is called maximal …

In this paper, we design user-centric obfuscation mechanisms that impose the minimum
utility loss for guaranteeing user's privacy. We optimize utility subject to a joint guarantee of …

We present a novel approach to proving the absence of timing channels. The idea is to
partition the program's execution traces in such a way that each partition component is …

Given two discrete random variables X and Y, an operational approach is undertaken to
quantify the “leakage” of information from X to Y. The resulting measure ℒ (X→ Y) is called …

Protecting sensitive information from improper disclosure is a fundamental security goal. It is
complicated, and difficult to achieve, often because of unavoidable or even unpredictable …

We introduce a privacy measure called pointwise maximal leakage, generalizing the pre-
existing notion of maximal leakage, which quantifies the amount of information leaking about …

Hardware vulnerabilities are often due to design mistakes because the designer does not
sufficiently consider potential security vulnerabilities at the design stage. As a result, various …

We introduce a gain function viewpoint of information leakage by proposing maximal-
leakage, a rich class of operationally meaningful leakage measures that subsumes recently …

The problem of publishing privacy-guaranteed data for hypothesis testing is studied using
the maximal leakage (ML) as a metric for privacy and the type-II error exponent as the utility …