# Josée DesharnaisLaval University | ULAVAL · Department of Computer Science

Josée Desharnais

## About

53

Publications

3,455

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2,259

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Introduction

**Skills and Expertise**

Additional affiliations

December 2000 - present

## Publications

Publications (53)

Cops and Robbers games have been studied for the last few decades in computer science and mathematics. As in general pursuit evasion games, pursuers (cops) seek to capture evaders (robbers); however, players move in turn and are constrained to move on a discrete structure, usually a graph, and know the exact location of their opponent. In 2017, Bon...

Cops and Robbers games have been studied for the last few decades in computer science and mathematics. As in general pursuit evasion games, pursuers (cops) seek to capture evaders (robbers); however, players move in turn and are constrained to move on a discrete structure, usually a graph, and know the exact location of their opponent. In 2017, Bon...

We give a discretization technique that allows one to check reachability properties in a family of continuous-state processes. We consider a sub-family of labelled Markov processes (LMP), whose transitions can be defined by uniform distributions, and simple reachability formulas.

We present a novel progress-sensitive, flow-sensitive hybrid information-flow control monitor for an imperative interactive language. Progress-sensitive information-flow control is a strong information security guarantee which ensures that a program's progress (or lack of) does not leak information. Flow-sensitivity means that this strong security...

In order to protect Android users and their information, we have developed a lightweight malware detection tool for Android called Andrana. It leverages machine learning techniques and static analysis to determine, with an accuracy of 94.90%, if an application is malicious. Its analysis can be performed directly on a mobile device in less than a se...

In order to protect Android users and their information, we have developed a lightweight malware detection tool for Android called Andrana. It leverages machine learning techniques and static analysis to determine, with an accuracy of 94.90%, if an application is malicious. Its analysis can be performed directly on a mobile device in less than a se...

We present a novel progress-sensitive, flow-sensitive hybrid information-flow control monitor for an imperative interactive language. Progress-sensitive information-flow control is a strong information security guarantee which ensures that a program’s progress (or lack of) does not leak information. Flow-sensitivity means that this strong security...

We present a novel progress-sensitive, flow-sensitive hybrid information-flow control monitor for an imperative interactive language. Progress-sensitive information-flow control is a strong information security guarantee which ensures that a program's progress (or lack of) does not leak information. Flow-sensitivity means that this strong security...

In search theory, the goal of the Optimal Search Path (OSP) problem is to find a finite length path maximizing the probability that a searcher detects a lost wanderer on a graph. We propose to bound the probability of finding the wanderer in the remaining search time by relaxing the problem into a stochastic game of cop and robber from graph theory...

In search theory, the goal of the Optimal Search Path (OSP) problem is to find a finite length path maximizing the probability that a searcher detects a lost wanderer on a graph. We propose to bound the probability of finding the wanderer in the remaining search time by relaxing the problem into a stochastic game of cop and robber from graph theory...

In search theory, the goal of the Optimal Search Path (OSP) problem is to find a finite length path maximizing the probability that a searcher detects a lost wanderer on a graph. We propose to bound the probability of finding the wanderer in the remaining search time by relaxing the problem into a stochastic game of cop and robber from graph theory...

In the Optimal Search Path problem from search theory, the objective is to find a finite length searcher's path that maximizes the probability of detecting a lost wanderer on a graph. We introduce a novel bound on the probability of finding the wanderer in the remaining search time and discuss how this bound is derived from a relaxation of the prob...

It is with great emotion that I write this tribute to Prakash. The minute I set foot into his office was one of those rare pivotal moments where one’s future changes. The path he led me on was exceptional and fascinating. From a somewhat purposeless dreamy math student, he smoothly transformed me into a critical part of what seemed and would become...

This paper presents an approach to enforce information flow policies using a multi-valued type-based analysis followed by an instru-mentation when needed. The target is a core imperative language. Our approach aims at reducing false positives generated by static analysis, and at reducing execution overhead by instrumenting only when needed. False p...

Checking if a given system implementation respects its specification is often done by
proving that the two are “equivalent”. The equivalence is chosen, in particular, for its
computability and of course for its meaning, that is, for its adequacy with what is
observable from the two systems (implementation and specification). Trace equivalence is
ea...

This paper presents an approach to enforce information flow policies using a three-valued type-based analysis on a core imperative language. Our analysis aims first at reducing false positives generated by static analysis, and second at preparing for instrumentation. False positives arise in the analysis of real computing systems when some informat...

This paper shows how to compute, for probabilistic hybrid systems, the clock
approximation and linear phase-portrait approximation that have been proposed
for non probabilistic processes by Henzinger et al. The techniques permit to
define a rectangular probabilistic process from a non rectangular one, hence
allowing the model-checking of any class...

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 bisimulation and simulation on PAs. We give logical
characterisations of these notions by choosing suitable logics which differ
from the elementary ones, L with negation and L...

This paper establishes a Stone-type duality between specifications and infLMPs. An infLMP is a probabilistic process whose transitions satisfy super-additivity instead of additivity. Interestingly, its simple structure can encode a mix of probabilistic and non-deterministic behavior, which, as we show, is strongly related to another well-known such...

We compare two models of processes involving uncountable space. Labelled Markov processes are probabilistic transition systems
that can have uncountably many states, but still make discrete time steps. The probability measures on the state space may
have uncountable support. Hybrid processes are a combination of a continuous space process that evo...

We investigate weak bisimulation of probabilistic systems in the presence of nondeterminism, i.e. labelled concurrent Markov chains (LCMC) with silent transitions. We build on the work of Philippou, Lee and Sokolsky [17] for finite state LCMCs. Their definition of weak bisimulation destroys the additivity property of the probability distributions,...

We investigate weak bisimulation of probabilistic systems in the presence of nondeterminism, i.e. labelled concurrent Markov chains (LCMC) with silent transitions. We develop an approach based on allowing convex combinations of computations, similar to Segala and Lynch’s use of randomized schedulers.The definition of weak bisimulation destroys the...

We propose a new approach for estimating the difference between two partially observable dynamical systems. We assume that
one can interact with the systems by performing actions and receiving observations. The key idea is to define a Markov Decision
Process (MDP) based on the systems to be compared, in such a way that the optimal value of the MDP...

This paper establishes a Stone-type duality between specifications and infLMPs. An infLMP is a probabilistic process whose
transitions satisfy super-additivity instead of additivity. Interestingly, its simple structure can encode a mix of probabilistic
and non-deterministic behaviors. Our duality shows that an infLMP can be considered as a demonic...

We tackle the problem of non robustness of simulation and bisimulation when dealing with probabilistic processes. It is important to ignore tiny deviations in probabilities because these often come from experiments or estimations. A few approaches have been proposed to treat this issue, for example metrics to quantify the non bisimilarity (or close...

In the context of probabilistic verification, we provide a new notion of trace-equivalence divergence between pairs of Labelled
Markov processes. This divergence corresponds to the optimal value of a particular derived Markov Decision Process. It can
therefore be estimated by Reinforcement Learning methods. Moreover, we provide some PAC-guarantees...

We introduce a new notion of bisimulation, called event bisimulation on labelled Markov processes (LMPs) and compare it with the, now standard, notion of probabilistic bisimulation, originally due to Larsen and Skou. Event bisimulation uses a sub σ-algebra as the basic carrier of information rather than an equivalence relation. The resulting notion...

This paper reports on and discusses three notions of approximation for Labelled Markov Processes that have been developed last year. The three schemes are improvements over former constructions [11,12] in the sense that they define approximants that capture more properties than before and that converge faster to the approximated process. One scheme...

The notion of process equivalence of probabilistic processes is sensitive to the exact probabilities of transitions. Thus, a slight change in the transition probabilities will result in two equivalent processes being deemed no longer equivalent. This instability is due to the quantitative nature of probabilistic processes. In a situation where the...

The notion of process equivalence of probabilistic processes is sensitive to the exact probabilities of transitions. Thus, a slight change in the transition probabilities will result in two equivalent processes being deemed no longer equivalent. This instability is due to the quantitative nature of probabilistic processes. In a situation where the...

This paper proposes a measure-theoretic reconstruction of the approximation schemes developed for labeled Markov processes: approximants are seen as quotients with respect to sets of temporal properties expressed in a simple logic. This gives the possibility of customizing approximants with respect to properties of interest and is thus an important...

We develop a new notion of approximation of labelled Markov processes based on the use of conditional expectations. The key idea is to approximate a system by a coarse-graining of the state space and using averages of the transition probabilities. This is unlike any of the previous notions based on the use of simulation. The resulting approximation...

We develop a theory of probabilistic continuous processes that is meant ultimately to be part of an interactive systems theory. Our model is a generalization of ordinary labelled transition systems to which we add probabilistic transitions. The four main contributions are: (1) a notion of bisimulation equivalence and simulation preorder, (2) a logi...

otone operators seems possible. We might pursue this option in the future. # Corresponding author : Equipe PPS, Universite Paris 7 Denis Diderot, Case 7014, 2 Place Jussieu 75251 PARIS Cedex 05, Vincent.Danos@pps.jussieu.fr 1 Preliminaries Definition 1 (LMP) = (S, #, h : L [0, 1]) is a Labelled Markov Process (LMP) if (S, #) is a measurable space,...

In this paper we introduce a new class of labelled transition systems—labelled Markov processes— and define bisimulation for them. Labelled Markov processes are probabilistic labelled transition systems where the state space is not necessarily discrete. We assume that the state space is a certain type of common metric space called an analytic space...

Labelled Markov processes are probabilistic versions of labelled transition systems. In general, the state space of a labelled Markov process may be a continuum. In this paper, we study approximation techniques for continuous-state labelled Markov processes. We show that the collection of labelled Markov processes carries a Polish-space structure w...

In a recent paper Baier et al. [Lecture Notes in Computer Science, Springer-Verlag, 2000, p. 358] analyzed a new way of model-checking formulas of a logic for continuous-time processes—called continuous stochastic logic (henceforth CSL)—against continuous-time Markov chains—henceforth CTMCs. One of the important results of that paper was the proof...

We observe that equivalence is not a robust concept in the presence of numerical information - such as probabilities-in the model. We develop a metric analogue of weak bisimulation in the spirit of our earlier work on metric analogues for strong bisimulation. We give a fixed point characterization of the metric. This makes available conductive reas...

In this paper we introduce a new class of labelled transition systems-Labelled Markov Processes-and define bisimulation for them. Labelled Markov processes are probabilistic labelled transition systems where the state space is not necessarily discrete, it could be the reals, for example. We assume that it is a Polish space (the underlying topologic...

We study approximate reasoning about continuous-state labeled Markov processes. We show how to approximate a labeled Markov process by a family of finite-state labeled Markov chains. We show that the collection of labeled Markov processes carries a Polish space structure with a countable basis given by finite state Markov chains with rational proba...

We study approximate reasoning about continuous-state labeled Markov processes. We show how to approximate a labeled Markov process by a family of finite-state labeled Markov chains. We show that the collection of labeled Markov processes carries a Polish space structure with a countable basis given by finite state Markov chains with rational proba...

Partial Labeled Markov Chains are simultaneously generalizations of process algebra and of traditional Markov chains. They provide a foundation for interacting discrete probabilistic systems, the interaction being synchronization on labels as in process algebra. Existing notions of process equivalence are too sensitive to the exact probabilities of...

This paper gives a logical characterization of probabilistic
bisimulation for Markov processes. Bisimulation can be characterized by
a very weak modal logic. The most striking feature is that one has no
negation or any kind of negative proposition. Bisimulation can be
characterized by several inequivalent logics; we report five in this
paper and th...