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 …

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 …

In computer security, it is frequently necessary in practice to accept some leakage of
confidential information. This motivates the development of theories of Quantitative …

We combine Kronecker products, and quantitative information flow, to give a novel formal
analysis for the fine-grained verification of utility in complex privacy pipelines. The …

We study the privacy-utility trade-off in the context of metric differential privacy. Ghosh et al.
introduced the idea of universal optimality to characterise the “best” mechanism for a certain …

Quantitative information flow aims to assess and control the leakage of sensitive information
by computer systems. A key insight in this area is that no single leakage measure is …

In order to protect user data while maintaining application functionality, encrypted databases
can use specialized cryptography such as property-revealing encryption, which allows a …

Quantitative Information Flow (QIF) and Differential Privacy (DP) are both concerned with the
protection of sensitive information, but they are rather different approaches. In particular, QIF …

We consider a game-theoretic setting to model the interplay between attacker and defender
in the context of information flow, and to reason about their optimal strategies. In contrast …

This work presents an axiomatization for entropy based on an extension of concavity called
core-concavity. We show that core-concavity characterizes the largest class of functions for …