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Model Checking Algorithms for Hyperproperties (Invited Paper)

Authors :
Bernd Finkbeiner
Source :
Verification, Model Checking, and Abstract Interpretation-22nd International Conference, VMCAI 2021, Copenhagen, Denmark, January 17–19, 2021, Proceedings, Lecture Notes in Computer Science, Lecture Notes in Computer Science-Verification, Model Checking, and Abstract Interpretation, Lecture Notes in Computer Science ISBN: 9783030670665
Publication Year :
2021

Abstract

Hyperproperties generalize trace properties by expressing relations between multiple computations. Hyperpropertes include policies from information-flow security, like observational determinism or non-interference, and many other system properties including promptness and knowledge. In this paper, we give an overview on the model checking problem for temporal hyperlogics. Our starting point is the model checking algorithm for HyperLTL, a reduction to Buchi automata emptiness. This basic construction can be extended with propositional quantification, resulting in an algorithm for HyperQPTL. It can also be extended with branching time, resulting in an algorithm for HyperCTL*. However, it is not possible to have both extensions at the same time: the model checking problem of HyperQCTL* is undecidable. An attractive compromise is offered by MPL[E], i.e., monadic path logic extended with the equal-level predicate. The expressiveness of MPL[E] falls strictly between that of HyperCTL* and HyperQCTL*. MPL[E] subsumes both HyperCTL* and HyperKCTL*, the extension of HyperCTL* with the knowledge operator. We show that the model checking problem for MPL[E] is still decidable.

Details

ISBN :
978-3-030-67066-5
978-3-030-67067-2
ISSN :
03029743 and 16113349
ISBNs :
9783030670665 and 9783030670672
Database :
OpenAIRE
Journal :
Verification, Model Checking, and Abstract Interpretation - 22nd International Conference, VMCAI 2021, Copenhagen, Denmark, January 17–19, 2021, Proceedings
Accession number :
edsair.doi.dedup.....8e0ba2d0b5860a0e0cf8bf4fd206062d
Full Text :
https://doi.org/10.1007/978-3-030-67067-2_1