Data-Dependent Confidentiality in DCR Graphs
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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We present DCRSec, a confidentially aware declarative process language with data that employs data-dependent security levels and an information flow monitor that prevents the violation of information flow policies. Data-dependent security levels have been used to shape precise information flow policies and properly identify security compartments. We use an illustrative example to show that it also models process instances in a flexible but precise way. The semantics of the language is based on a version of the Dynamic Condition Response Graph language, which allows for declaring data-aware, event-based processes with finitary and infinitary computations subject to liveness properties and dynamically spawned sub-processes. The key technical contribution is to provide a termination-insensitive information flow monitor and prove non-interference, a soundness property, and transparency in all traces of DCRSec processes.
Originalsprog | Engelsk |
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Titel | Proceedings of the 25th International Symposium on Principles and Practice of Declarative Programming (PPDP 2023) |
Antal sider | 13 |
Forlag | Association for Computing Machinery |
Publikationsdato | 2023 |
Artikelnummer | 7 |
ISBN (Elektronisk) | 979-8-4007-0812-1 |
DOI | |
Status | Udgivet - 2023 |
Begivenhed | 25th International Symposium on Principles and Practice of Declarative Programming, PPDP 2023 - As part of the ACM SIGPLAN conference on Systems, Programming, Languages, and Applications: Software for Humanity, SPLASH 2023, including LOPSTR 2023 - Lisbon, Portugal Varighed: 22 okt. 2023 → 23 okt. 2023 |
Konference
Konference | 25th International Symposium on Principles and Practice of Declarative Programming, PPDP 2023 - As part of the ACM SIGPLAN conference on Systems, Programming, Languages, and Applications: Software for Humanity, SPLASH 2023, including LOPSTR 2023 |
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Land | Portugal |
By | Lisbon |
Periode | 22/10/2023 → 23/10/2023 |
Bibliografisk note
Funding Information:
Funded by FCT/MCTES SFRH/BD/149043/2019, by EU Horizon Europe under Grant, Agreement no. 101093006 (TaRDIS), by NOVA LINCS (FCT UIDB/04516/2020), and by Independent Research Fund Denmark, Grant no. 9131-00077B (PAPRiCaS).
Publisher Copyright:
© 2023 Owner/Author.
ID: 390399152