Flavors of sequential information flow

Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. 2022. Flavors of sequential information flow. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). VMCAI: Verifcation, Model Checking, and Abstract Interpretation, LNCS, vol. 13182, 1–19.

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Author
Bartocci, Ezio; Ferrere, ThomasISTA ; Henzinger, Thomas AISTA ; Nickovic, DejanISTA; Da Costa, Ana Oliveira
Department
Series Title
LNCS
Abstract
We study the problem of specifying sequential information-flow properties of systems. Information-flow properties are hyperproperties, as they compare different traces of a system. Sequential information-flow properties can express changes, over time, in the information-flow constraints. For example, information-flow constraints during an initialization phase of a system may be different from information-flow constraints that are required during the operation phase. We formalize several variants of interpreting sequential information-flow constraints, which arise from different assumptions about what can be observed of the system. For this purpose, we introduce a first-order logic, called Hypertrace Logic, with both trace and time quantifiers for specifying linear-time hyperproperties. We prove that HyperLTL, which corresponds to a fragment of Hypertrace Logic with restricted quantifier prefixes, cannot specify the majority of the studied variants of sequential information flow, including all variants in which the transition between sequential phases (such as initialization and operation) happens asynchronously. Our results rely on new equivalences between sets of traces that cannot be distinguished by certain classes of formulas from Hypertrace Logic. This presents a new approach to proving inexpressiveness results for HyperLTL.
Publishing Year
Date Published
2022-01-14
Proceedings Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Acknowledgement
This work was funded in part by the Wittgenstein Award Z211-N23 of the Austrian Science Fund (FWF) and by the FWF project W1255-N23.
Volume
13182
Page
1-19
Conference
VMCAI: Verifcation, Model Checking, and Abstract Interpretation
Conference Location
Philadelphia, PA, United States
Conference Date
2022-01-16 – 2022-01-18
ISSN
eISSN
IST-REx-ID

Cite this

Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. Flavors of sequential information flow. In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 13182. Springer Nature; 2022:1-19. doi:10.1007/978-3-030-94583-1_1
Bartocci, E., Ferrere, T., Henzinger, T. A., Nickovic, D., & Da Costa, A. O. (2022). Flavors of sequential information flow. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13182, pp. 1–19). Philadelphia, PA, United States: Springer Nature. https://doi.org/10.1007/978-3-030-94583-1_1
Bartocci, Ezio, Thomas Ferrere, Thomas A Henzinger, Dejan Nickovic, and Ana Oliveira Da Costa. “Flavors of Sequential Information Flow.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13182:1–19. Springer Nature, 2022. https://doi.org/10.1007/978-3-030-94583-1_1.
E. Bartocci, T. Ferrere, T. A. Henzinger, D. Nickovic, and A. O. Da Costa, “Flavors of sequential information flow,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Philadelphia, PA, United States, 2022, vol. 13182, pp. 1–19.
Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. 2022. Flavors of sequential information flow. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). VMCAI: Verifcation, Model Checking, and Abstract Interpretation, LNCS, vol. 13182, 1–19.
Bartocci, Ezio, et al. “Flavors of Sequential Information Flow.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13182, Springer Nature, 2022, pp. 1–19, doi:10.1007/978-3-030-94583-1_1.

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