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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" }