Hyperproperties are properties that describe the correctness of a system as a relation between multiple executions. Hyperproperties generalize trace properties and include information-flow security requirements, like noninterference, as well as requirements like symmetry, partial observation, robustness, and fault tolerance. We initiate the study of the specification and verification of hyperproperties of Markov decision processes (MDPs). We introduce the temporal logic PHL (Probabilistic Hyper Logic), which extends classic probabilistic logics with quantification over schedulers and traces. PHL can express a wide range of hyperproperties for probabilistic systems, including both classical applications, such as probabilistic noninterference, and novel applications in areas such as
robotics and planning. While the model checking problem for PHL is in
general undecidable, we provide methods both for proving and for refuting
formulas from a fragment of the logic. The fragment includes many
probabilistic hyperproperties of interest.
History
Preferred Citation
Rayna Dimitrova, Bernd Finkbeiner and Hazem Torfah. Probabilistic Hyperproperties of Markov Decision Processes. In: International Symposium on Automated Technology for Verification and Analysis (ATVA). 2020.
Primary Research Area
Reliable Security Guarantees
Name of Conference
International Symposium on Automated Technology for Verification and Analysis (ATVA)
Legacy Posted Date
2020-12-07
Open Access Type
Green
BibTeX
@inproceedings{cispa_all_3320,
title = "Probabilistic Hyperproperties of Markov Decision Processes",
author = "Dimitrova, Rayna and Finkbeiner, Bernd and Torfah, Hazem",
booktitle="{International Symposium on Automated Technology for Verification and Analysis (ATVA)}",
year="2020",
}