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Machine-Checking the Universal Verifiability of ElectionGuard

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Secure IT Systems (NordSec 2020)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12556))

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Abstract

ElectionGuard is an open source set of software components and specifications from Microsoft designed to allow the modification of a number of different e-voting protocols and products to produce public evidence (transcripts) which anyone can verify. The software uses ElGamal, homomorphic tallying and sigma protocols to enable public scrutiny without adversely affecting privacy. Some components have been formally verified (machine-checked) to be free of certain software bugs but there was no formal verification of their cryptographic security.

Here, we present a machine-checked proof of the verifiability guarantees of the transcripts produced according to the ElectionGuard specification. We have also extracted an executable version of the verifier specification, which we proved to be secure, and used it to verify election transcripts produced by ElectionGuard. Our results show that our implementation is of similar efficiency to existing implementations.

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Notes

  1. 1.

    https://github.com/microsoft/electionguard/wiki/Informal/ElectionGuardSpecificationV0.85.pdf.

  2. 2.

    For simplicity, we describe a fairly narrow use case of ElectionGuard.

  3. 3.

    http://heartbleed.com/.

  4. 4.

    https://github.com/microsoft/electionguard-verifier.

  5. 5.

    https://github.com/microsoft/electionguard/wiki/Informal/ElectionGuardSpecifi-cationV0.85.pdf.

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Acknowledgments

This work was supported by the Luxembourg National Research Fund (FNR) and the Research Council of Norway for the joint project SURCVS.

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Correspondence to Thomas Haines .

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Haines, T., Goré, R., Stodart, J. (2021). Machine-Checking the Universal Verifiability of ElectionGuard. In: Asplund, M., Nadjm-Tehrani, S. (eds) Secure IT Systems. NordSec 2020. Lecture Notes in Computer Science(), vol 12556. Springer, Cham. https://doi.org/10.1007/978-3-030-70852-8_4

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  • DOI: https://doi.org/10.1007/978-3-030-70852-8_4

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