Affiliation:
1. Duke University, Durham, NC
2. Iowa State University, Ames, IA
Abstract
Many important properties of cyber-physical systems (CPS) are defined upon the relationship between multiple executions simultaneously in continuous time. Examples include probabilistic fairness and sensitivity to modeling errors (i.e., parameters changes) for real-valued signals. These requirements can only be specified by
hyperproperties
. In this article, we focus on verifying probabilistic hyperproperties for CPS. To cover a wide range of modeling formalisms, we first propose a general model of probabilistic uncertain systems (PUSs) that unify commonly studied CPS models such as
continuous-time Markov chains
(CTMCs) and
probabilistically parametrized Hybrid I/O Automata
(P
2
HIOA). To formally specify hyperproperties, we propose a new temporal logic,
hyper probabilistic signal temporal logic
(HyperPSTL) that serves as a hyper and probabilistic version of the conventional signal temporal logic (STL). Considering the complexity of real-world systems that can be captured as PUSs, we adopt a
statistical model checking
(SMC) approach for their verification. We develop a new SMC technique based on the direct computation of significance levels of statistical assertions for HyperPSTL specifications, which requires no
a priori
knowledge on the indifference margin. Then, we introduce SMC algorithms for HyperPSTL specifications on the joint probabilistic distribution of multiple paths, as well as specifications with nested probabilistic operators quantifying different paths, which cannot be handled by existing SMC algorithms. Finally, we show the effectiveness of our SMC algorithms on CPS benchmarks with varying levels of complexity, including the Toyota Powertrain Control System.
Funder
Office of Naval Research
Air Force Office of Scientific Research
National Science Foundation
Publisher
Association for Computing Machinery (ACM)
Subject
Hardware and Architecture,Software
Cited by
28 articles.
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