Talks and Poster Presentations (with Proceedings-Entry):
E. Abraham, E. Bartocci, B. Bonakdarpour, O. Dobe:
"Parameter Synthesis for Probabilistic Hyperproperties";
Talk: Proc. of LPAR 2020: the 23rd International Conference on Logic for Programming,
Alicante, Spain (Virtual due to covid19);
- 2020-05-27; in: "Proc. of LPAR 2020: the 23rd International Conference on Logic for Programming",
In this paper, we study the parameter synthesis problem for probabilistic hyperproper- ties. A probabilistic hyperproperty stipulates quantitative dependencies among a set of executions. In particular, we solve the following problem: given a probabilistic hyperprop- erty ψ and discrete-time Markov chain D with parametric transition probabilities, compute regions of parameter configurations that instantiate D to satisfy ψ, and regions that lead to violation. We address this problem for a fragment of the temporal logic HyperPCTL that allows expressing quantitative reachability relation among a set of computation trees. We illustrate the application of our technique in the areas of differential privacy, probabilistic nonintereference, and probabilistic conformance.
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
Created from the Publication Database of the Vienna University of Technology.