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Compositional Analysis of Protocol Equivalence in the Applied π-Calculus Using Quasi-open Bisimilarity

Published: 06 September 2021 Publication History

Abstract

This paper shows that quasi-open bisimilarity is the coarsest bisimilarity congruence for the applied π-calculus. Furthermore, we show that this equivalence is suited to security and privacy problems expressed as an equivalence problem in the following senses: (1) being a bisimilarity is a safe choice since it does not miss attacks based on rich strategies; (2) being a congruence it enables a compositional approach to proving certain equivalence problems such as unlinkability; and (3) being the coarsest such bisimilarity congruence it can establish proofs of some privacy properties where finer equivalences fail to do so.

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    cover image Guide Proceedings
    Theoretical Aspects of Computing – ICTAC 2021: 18th International Colloquium, Virtual Event, Nur-Sultan, Kazakhstan, September 8–10, 2021, Proceedings
    Sep 2021
    406 pages
    ISBN:978-3-030-85314-3
    DOI:10.1007/978-3-030-85315-0
    Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

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    Springer-Verlag

    Berlin, Heidelberg

    Publication History

    Published: 06 September 2021

    Author Tags

    1. Cryptographic calculi
    2. Bisimilarity
    3. Security
    4. Privacy
    5. Compositionality

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