Alessandra Di Pierro

Learn More
We address the problem of characterising the security of a program against unauthorised information flows. Classical approaches are based on non-interference models which depend ultimately on the notion of process equivalence. In these models confidentiality is an absolute property stating the absence of any illegal information flow. We present a model in(More)
We present a technique for measuring the security of a system which relies on a probabilistic process algebraic formalisation of noninterference. We define a mathematical model for this technique which consists of a linear space of processes and linear transformations on them. In this model the measured quantity corresponds to the norm of a suitably defined(More)
This paper investigates a probabilistic version of the concurrent constraint programming paradigm (CCP). The aim is to introduce the possibility to formulate so called \randomised algorithms" within the CCP framework. Diierently from common approaches in (imperative) high-level programming languages, which rely on some kind of random() function, we(More)
Synopsis Algorithms where the ow of information is determined by an element of random choice (a \coin ipping" device), aka randomised algorithms, have known in the last decade a tremendous growth of interest, especially in the eld of complexity theory. Up to now such algorithms have been implemented mostly by means of probabilistic programs written in(More)
This paper investigates a probabilistic version of the concurrent constraint programming paradigm (CCP). The aim is to introduce the possibility to formulate so called \randomised algorithms" within the CCP framework. Our approach incorporates randomness directly within the (operational) semantics instead of referring to an \external" function or procedure(More)
We present a method for approximating the semanti s of probabilisti programs to the purpose of onstru ting semanti s-based analyses of su h programs. The method resembles the one based on Galois onne tion as developed in the Cousot framework for abstra t interpretation. The main di eren e between our approa h and the standard theory of abstra t(More)
Classical Constraint Handling Rules (CHR) provide a powerful tool for specifying and implementing constraint solvers and programs. The rules of CHR rewrite constraints (non-deterministically) into simpler ones until they are solved. In this paper we introduce an extension of Constraint Handling Rules (CHR), namely Probabilistic CHRs (PCHR). These allow the(More)