Danny Bøgsted Poulsen

Statistical model checking for networks of priced timed automata

This paper offers a natural stochastic semantics of Networks of Priced Timed Automata (NPTA) based on races between components. The semantics provides the basis for satisfaction of probabilistic Weighted CTL properties (PWCTL), conservatively extending the classical satisfaction of timed automata with respect to TCTL. In particular the extension allows for hard real-time properties of timed automata expressible in TCTL to be refined by performance properties, e.g. in terms of probabilistic guarantees of time- and cost-bounded properties. A second contribution of the paper is the application of Statistical Model Checking (SMC) to efficiently estimate the correctness of non-nested PWCTL model checking problems with a desired level of confidence, based on a number of independent runs of the NPTA. In addition to applying classical SMC algorithms, we also offer an extension that allows to efficiently compare performance properties of NPTAs in a parametric setting. The third contribution is an efficient tool implementation of our result and applications to several case studies.

UPPAAL-SMC: Statistical Model Checking for Priced Timed Automata ∗

This paper offers a survey of UPPAAL-SMC, a major extension of the real-time verification tool UPPAAL. UPPAAL-SMC allows for the efficient analysis of performance properties of networks of priced timed automata under a natural stochastic semantics. In particular, U PPAAL-SMC relies on a series of extensions of the statistical model checking app roach generalized to handle real-time systems and estimate undecidable problems. UPPAAL-SMC comes together with a friendly user interface that allows a user to specify complex problems in an efficient manner as well as to get feedback in the form of probability distributions and compare probabilities to analyze performance aspects of systems. The focus of the survey is on the evolution of the tool ‐ including modeling and specification formalisms as well as techniques applied ‐ tog ether with applications of the tool to case studies.

Statistical Model Checking for Stochastic Hybrid Systems

This paper presents novel extensions and applications of the UPPAAL-SMC model checker. The extensions allow for statistical model checking of stochastic hybrid systems. We show how our race-based stochastic semantics extends to networks of hybrid systems, and indicate the integration technique applied for implementing this semantics in the UPPAAL-SMC simulation engine. We report on two applications of the resulting tool-set coming fr om systems biology and energy aware buildings.

Checking and distributing statistical model checking

In this paper we propose a general framework for distributed statistical model checking of networks of priced timed automata. The first contribution is a new algorithm to distribute sequential hypothesis testing without introducing bias in the results. The second contribution is an implementation of this algorithm in Uppaal. The major contribution is an experimental and analytical evaluation of the approach through case studies, including an analysis of the SMC algorithm itself.

Monitor-Based statistical model checking for weighted metric temporal logic

We present a novel approach and implementation for analysing weighted timed automata (WTA) with respect to the weighted metric temporal logic (WMTL≤). Based on a stochastic semantics of WTAs, we apply statistical model checking (SMC) to estimate and test probabilities of satisfaction with desired levels of confidence. Our approach consists in generation of deterministic monitors for formulas in WMTL≤, allowing for efficient SMC by run-time evaluation of a given formula. By necessity, the deterministic observers are in general approximate (over- or under-approximations), but are most often exact and experimentally tight. The technique is implemented in the new tool Casaal. that we seamlessly connect to Uppaal-smc. in a tool chain. We demonstrate the applicability of our technique and the efficiency of our implementation through a number of case-studies.

Runtime verification of biological systems

Complex computational systems are ubiquitous and their study increasingly important. Given the ease with which it is possible to construct large systems with heterogeneous technology, there is strong motivation to provide automated means to verify their safety, efficiency and reliability. In another context, biological systems are supreme examples of complex systems for which there are no design specifications. In both cases it is usually difficult to reason at the level of the description of the systems and much more convenient to investigate properties of their executions. To demonstrate runtime verification of complex systems we apply statistical model checking techniques to a model of robust biological oscillations taken from the literature. The model demonstrates some of the mechanisms used by biological systems to maintain reliable performance in the face of inherent stochasticity and is therefore instructive. To perform our investigation we use two recently developed SMC platforms: that incorporated in Uppaal and Plasma. Uppaal-smc offers a generic modeling language based on stochastic hybrid automata, while Plasma aims at domain specific support with the facility to accept biological models represented in chemical syntax.

Rewrite-Based Statistical Model Checking of WMTL

We present a new technique for verifying Weighted Metric Temporal Logic (WMTL) properties of Weighted Timed Automata. Our approach relies on Statistical Model Checking combined with a new monitoring algorithm based on rewriting rules. Contrary to existing monitoring approaches for WMTL ours is exact. The technique has been implemented in the statistical model checking engine of Uppaal and experiments indicate that the technique performs faster than existing approaches and leads to more accurate results.

Statistical model checking of dynamic networks of stochastic hybrid automata

In this paper we present a modelling formalism for dynamic networks of stochastic hybrid automata. In particular, our formalism is based on primitives for the dynamic creation and termination of hybrid automata components during the execution of a system. In this way we allow for natural modelling of concepts such as multiple threads found in various programming paradigms, as well as the dynamic evolution of biological systems. We provide a natural stochastic semantics of the modelling formalism based on re- peated output races between the dynamic evolving components of a system. As specification language we present a quantified extension of the logic Metric Tempo- ral Logic (MTL). As a main contribution of this paper, the statistical model checking engine of U PPAAL has been extended to the setting of dynamic networks of hybrid systems and quantified MTL. We demonstrate the usefulness of the extended for- malisms in an analysis of a dynamic version of the well-known Train Gate example, as well as in natural monitoring of a MTL formula, where observations may lead to dynamic creation of monitors for sub-formulas.

Modelling Attack-defense Trees Using Timed Automata

Performing a thorough security risk assessment of an organisation has always been challenging, but with the increased reliance on outsourced and off-site third-party services, i.e., “cloud services”, combined with internal (legacy) IT-infrastructure and -services, it has become a very difficult and time-consuming task. One of the traditional tools available to ease the burden of performing a security risk assessment and structure security analyses in general is attack trees, a tree-based formalism inspired by fault trees, a well-known formalism used in safety engineering. In this paper we study an extension of traditional attack trees, called attack-defense trees, in which not only the attacker’s actions are modelled, but also the defensive actions taken by the attacked party. In this work we use the attack-defense tree as a goal an attacker wants to achieve, and separate the behaviour of the attacker and defender from the attack-defense-tree. We give a fully stochastic timed semantics for the behaviour of the attacker by introducing attacker profiles that choose actions probabilistically and execute these according to a probability density. Lastly, the stochastic semantics provides success probabilitites for individual actions. Furthermore, we show how to introduce costs of attacker actions. Finally, we show how to automatically encode it all with a network of timed automata, an encoding that enables us to apply state-of-the-art model checking tools and techniques to perform fully automated quantitative and qualitative analyses of the modelled system.

Quantified Dynamic Metric Temporal Logic for Dynamic Networks of Stochastic Hybrid Automata

Multiprocessing systems are capable of running multiple processes concurrently. By now such systems have established themselves as the defacto standard for operating systems. At the core of an operating system is the ability to execute programs and as such there must be a primitive for instantiating new processes - also programs are allowed to die/terminate. Operating systems may allow the executing programs to split (spawn) into more computational threads in order to let programs take advantage of concurrent execution as well. One of the most used modelling languages, Timed Automata, is based on multiple automata interacting thus they easily model the concurrent execution of programs. However, this language assumes a fixed size system in the sense that automata cannot be created at will but must be instantiated when the overall system is created. This is in contrast with the fact that developers are able to create threads when needed. In this paper we present our continued work to incorporate spawning of threads into UPPAAL SMC. Our modelling language, Dynamic Networks of Stochastic Hybrid Automata, is essentially Timed Automata extended with a spawning primitive and a tear-down primitive. The dynamic creation of threads has the side-effect that it is no longer possible to use ordinary logics to specify behaviours of individual threads - because the threads no longer have unique names. In this paper we propose an extension of Metric Temporal Logic with means for quantifying over the dynamically created threads. This makes it possible to zoom in on individual threads and specify requirements to their future behaviour. Furthermore, we present a monitoring procedure for the logic based on rewriting formulas. The presented modelling language and the specification language have been implemented in UPPAAL SMC version 4.1.18.