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 …

We present CacheAudit, a versatile framework for the automatic, static analysis of cache
side channels. CacheAudit takes as input a program binary and a cache configuration and …

This paper addresses the problem of assessing nicotine dependence. The main objective is
to develop theory‐led suggestions for measures that will be relevant in the early phases of …

This paper introduces g-leakage, a rich generalization of the min-entropy model of
quantitative information flow. In g-leakage, the benefit that an adversary derives from a …

Differential privacy is a notion of privacy that has become very popular in the database
community. Roughly, the idea is that a randomized query mechanism provides sufficient …

In this work, the probability of an event under some joint distribution is bounded by
measuring it with the product of the marginals instead (which is typically easier to analyze) …

We investigate the problem of estimating a random variable Y under a privacy constraint
dictated by another correlated random variable X. When X and Y are discrete, we express …

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 …

The latency gap between caches and main memory has been successfully exploited for
recovering sensitive input to programs, such as cryptographic keys from implementation of …

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 …