A Categorical Approach to Secure Compilation

Stelios Tsampas; Andreas Nuyts; Dominique Devriese; Frank Piessens

doi:10.1007/978-3-030-57201-3_9

A Categorical Approach to Secure Compilation

Stelios Tsampas, Andreas Nuyts, Dominique Devriese, Frank Piessens

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

2 Citations (Scopus)

Abstract

We introduce a novel approach to secure compilation based on maps of distributive laws. We demonstrate through four examples that the coherence criterion for maps of distributive laws can potentially be a viable alternative for compiler security instead of full abstraction, which is the preservation and reflection of contextual equivalence. To that end, we also make use of the well-behavedness properties of distributive laws to construct a categorical argument for the contextual connotations of bisimilarity.

Original language	English
Title of host publication	Categorical Methods in Computer Science
Publisher	Springer
Pages	155-179
Number of pages	25
ISBN (Electronic)	978-3-030-57201-3
ISBN (Print)	978-3-030-57200-6
DOIs	https://doi.org/10.1007/978-3-030-57201-3_9
Publication status	Published - 2020
Event	Coalgebraic Methods in Computer Science - Dublin, Ireland Duration: 21 Sep 2020 → 19 Oct 2020 Conference number: 2020 https://www.coalg.org/cmcs20/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12094 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Workshop

Workshop	Coalgebraic Methods in Computer Science
Abbreviated title	CMCS
Country	Ireland
City	Dublin
Period	21/09/20 → 19/10/20
Internet address	https://www.coalg.org/cmcs20/

Access to Document

10.1007/978-3-030-57201-3_9Licence: CC BY

https://www.mendeley.com/catalogue/b85c9c44-27b3-3026-afe1-4c5b612566b4/

Cite this

Tsampas, S., Nuyts, A., Devriese, D., & Piessens, F. (2020). A Categorical Approach to Secure Compilation. In Categorical Methods in Computer Science (pp. 155-179). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12094 LNCS). Springer. https://doi.org/10.1007/978-3-030-57201-3_9

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title = "A Categorical Approach to Secure Compilation",

abstract = "We introduce a novel approach to secure compilation based on maps of distributive laws. We demonstrate through four examples that the coherence criterion for maps of distributive laws can potentially be a viable alternative for compiler security instead of full abstraction, which is the preservation and reflection of contextual equivalence. To that end, we also make use of the well-behavedness properties of distributive laws to construct a categorical argument for the contextual connotations of bisimilarity.",

author = "Stelios Tsampas and Andreas Nuyts and Dominique Devriese and Frank Piessens",

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doi = "10.1007/978-3-030-57201-3_9",

language = "English",

isbn = "978-3-030-57200-6",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "155--179",

booktitle = "Categorical Methods in Computer Science",

note = "Coalgebraic Methods in Computer Science, CMCS ; Conference date: 21-09-2020 Through 19-10-2020",

url = "https://www.coalg.org/cmcs20/",

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Tsampas, S, Nuyts, A, Devriese, D & Piessens, F 2020, A Categorical Approach to Secure Compilation. in Categorical Methods in Computer Science. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12094 LNCS, Springer, pp. 155-179, Coalgebraic Methods in Computer Science, Dublin, Ireland, 21/09/20. https://doi.org/10.1007/978-3-030-57201-3_9

A Categorical Approach to Secure Compilation. / Tsampas, Stelios; Nuyts, Andreas; Devriese, Dominique; Piessens, Frank.

Categorical Methods in Computer Science. Springer, 2020. p. 155-179 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12094 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

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