Publication detail

Deductive Controller Synthesis for Probabilistic Hyperproperties

ANDRIUSHCHENKO, R. BARTOCCI, E. ČEŠKA, M. FRANCESCO, P. SARAH, S.

Original Title

Deductive Controller Synthesis for Probabilistic Hyperproperties

Type

conference paper

Language

English

Original Abstract

Probabilistic hyperproperties specify quantitative relations between the probabilities of reaching different target sets of states from different initial sets of states. This class of behavioral properties is suitable for capturing important security, privacy, and system-level requirements. We propose a new approach to solve the controller synthesis problem for Markov decision processes (MDPs) and probabilistic hyperproperties. Our specification language builds on top of the logic HyperPCTL and enhances it with structural constraints over the synthesized controllers. Our approach starts from a family of controllers represented symbolically and defined over the same copy of an MDP. We then introduce an abstraction refinement strategy that can relate multiple computation trees and that we employ to prune the search space deductively. The experimental evaluation demonstrates that the proposed approach considerably outperforms HYPERPROB, a state-of-the-art SMT-based model checking tool for HyperPCTL. Moreover, our approach is the first one that is able to effectively combine probabilistic hyperproperties with additional intra-controller constraints (e.g. partial observability) as well as inter-controller constraints (e.g. agreements on a common action).

Keywords

Hyperproperties, Markov decision processes, abstraction refinement

Authors

ANDRIUSHCHENKO, R.; BARTOCCI, E.; ČEŠKA, M.; FRANCESCO, P.; SARAH, S.

Released

2. 8. 2023

Publisher

Springer Verlag

Location

Cham

ISBN

978-3-031-43834-9

Book

Quantitative Evaluation of SysTems

Edition

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Pages from

288

Pages to

306

Pages count

19

BibTex

@inproceedings{BUT185191,
  author="ANDRIUSHCHENKO, R. and BARTOCCI, E. and ČEŠKA, M. and FRANCESCO, P. and SARAH, S.",
  title="Deductive Controller Synthesis for Probabilistic Hyperproperties",
  booktitle="Quantitative Evaluation of SysTems",
  year="2023",
  series="Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
  volume="14287",
  pages="288--306",
  publisher="Springer Verlag",
  address="Cham",
  doi="10.1007/978-3-031-43835-6\{_}20",
  isbn="978-3-031-43834-9"
}