We present new algorithms for computing and approximating bisimulation metrics in Markov
Decision Processes (MDPs). Bisimulation metrics are an elegant formalism that capture …

Differential privacy is a notion of confidentiality that protects the privacy of individuals while
allowing useful computations on their private data. Deriving differential privacy guarantees …

Differential privacy is a notion of confidentiality that allows useful computations on sensible
data while protecting the privacy of individuals. Proving differential privacy is a difficult and …

Abstract f-divergences form a class of measures of distance between probability
distributions; they are widely used in areas such as information theory and signal …

Differential privacy is a promising approach to privacy preserving data analysis with a well-
developed theory for functions. Despite recent work on implementing systems that aim to …

Computational Indistinguishability Logic (CIL) is a logic for reasoning about cryptographic
primitives in computational models. It captures reasoning patterns that are common in …

Provable security. The goal of provable security is to verify rigorously the security of
cryptographic systems. A provable security argument proceeds in three steps: 1 Define a …

This thesis explores proofs by coupling from the perspective of formal verification. Long
employed in probability theory and theoretical computer science, these proofs construct …

We present relaxed notions of simulation and bisimulation on Probabilistic Automata (PA),
that allow some error epsilon. When epsilon is zero we retrieve the usual notions of …

Gossip protocols have been proposed as a robust and efficient method for disseminating
information throughout large-scale networks. In this paper, we propose a compositional …