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Open AccessJournal ArticleDOI

Stochastic Timed Automata

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TLDR
Correctness of the abstraction holds when automata are almost-surely fair, which it is shown, is the case for two large classes of systems, single- clock automata and so-called weak-reactive automata.
Abstract
A stochastic timed automaton is a purely stochastic process defined on a timed automaton, in which both delays and discrete choices are made randomly. We study the almost-sure model-checking problem for this model, that is, given a stochastic timed automaton A and a property $\Phi$, we want to decide whether A satisfies $\Phi$ with probability 1. In this paper, we identify several classes of automata and of properties for which this can be decided. The proof relies on the construction of a finite abstraction, called the thick graph, that we interpret as a finite Markov chain, and for which we can decide the almost-sure model-checking problem. Correctness of the abstraction holds when automata are almost-surely fair, which we show, is the case for two large classes of systems, single- clock automata and so-called weak-reactive automata. Techniques employed in this article gather tools from real-time verification and probabilistic verification, as well as topological games played on timed automata.

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Proceedings ArticleDOI

The Probabilistic Model Checking Landscape

TL;DR: This paper surveys the algorithmic verification of probabilistic models, in particular Probabilistic model checking, and provides an informal account of the main models, the underlying algorithms, applications from reliability and dependability analysis—and beyond—and describes recent developments towards automated parameter synthesis.
DissertationDOI

Truth or dare : quantitative security risk analysis via attack trees

Rajesh Kumar
TL;DR: This thesis provides a multi-faceted security analysis framework that is capable of answering a rich set of security questions such as cost-optimal attack scenarios for attackers, time-dependent attack probabilities, etc and proposes novel methods using the automata theoretic framework and relying on stochastic and statistical model checking.
Book ChapterDOI

The 10,000 Facets of MDP Model Checking

TL;DR: The manifold facets of this field of research are discussed by surveying the verification of various MDP extensions, rich classes of properties, and their applications by surveyed the basic ingredients of MDP model checking.
Proceedings ArticleDOI

Attack Trees for Security and Privacy in Social Virtual Reality Learning Environments

TL;DR: A novel framework to obtain quantitative assessments of threats and vulnerabilities for VRLEs is presented, based on the use cases from an actual social VRLE viz., vSocial, and the effectiveness of the attack tree modeling is demonstrated.
Journal ArticleDOI

Undecidability results for probabilistic automata

TL;DR: This paper provides streamlined constructions implying the most important negative results, including the celebrated inapproximability result of Condon and Lipton.
References
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Book

Introduction to Algorithms

TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Book ChapterDOI

Introduction to Algorithms

Xin-She Yang
TL;DR: This chapter provides an overview of the fundamentals of algorithms and their links to self-organization, exploration, and exploitation.
Journal ArticleDOI

A theory of timed automata

TL;DR: Alur et al. as discussed by the authors proposed timed automata to model the behavior of real-time systems over time, and showed that the universality problem and the language inclusion problem are solvable only for the deterministic automata: both problems are undecidable (II i-hard) in the non-deterministic case and PSPACE-complete in deterministic case.
Book

Probability and Measure

TL;DR: In this paper, the convergence of distributions is considered in the context of conditional probability, i.e., random variables and expected values, and the probability of a given distribution converging to a certain value.
Proceedings ArticleDOI

The temporal logic of programs

Amir Pnueli
TL;DR: A unified approach to program verification is suggested, which applies to both sequential and parallel programs, and the main proof method is that of temporal reasoning in which the time dependence of events is the basic concept.
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