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A Note on Risk-Limiting Bayesian Polling Audits for Two-Candidate Elections

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Financial Cryptography and Data Security (FC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12063))

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Abstract

This short paper provides a general form for a polling audit that is both Bayesian and risk-limiting: the Bayesian Risk-Limiting (Polling) Audit, which enables the use of a Bayesian approach to explore more efficient Risk-Limiting Audits. A numerical example illustrates the implications to practice.

This material is based upon work supported in part by NSF Award CNS 1421373.

Author was partially supported by Polish National Science Centre contract number DEC-2013/09/D/ST6/03927 and by Wroclaw University of Science and Technology [0401/0052/18].

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Notes

  1. 1.

    Philip Stark has mentioned a CLIP-like audit which does not use simulations as work in progress.

References

  1. Lindeman, M., Stark, P.B.: A gentle introduction to risk-limiting audits. IEEE Secur. Priv. 10(5), 42–49 (2012)

    Article  Google Scholar 

  2. Lindeman, M., Stark, P.B., Yates, V.S.: BRAVO: ballot-polling risk-limiting audits to verify outcomes. In: EVT/WOTE (2012)

    Google Scholar 

  3. Ottoboni, K., Stark, P.B., Lindeman, M., McBurnett, N.: Risk-limiting audits by stratified union-intersection tests of elections (SUITE). In: Krimmer, R., et al. (eds.) E-Vote-ID 2018. LNCS, vol. 11143, pp. 174–188. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00419-4_12

    Chapter  Google Scholar 

  4. Rivest, R.L.: ClipAudit–a simple post-election risk-limiting audit. arXiv:1701.08312

  5. Rivest, R.L., Shen, E.: A Bayesian method for auditing elections. In: EVT/WOTE (2012)

    Google Scholar 

  6. Vora, P.L.: Risk-limiting Bayesian polling audits for two candidate elections. CoRR abs/1902.00999 (2019). http://arxiv.org/abs/1902.00999

  7. Wald, A.: Sequential tests of statistical hypotheses. Ann. Math. Stat. 16(2), 117–186 (1945)

    Article  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, The George Washington University, Washington, DC, USA

    Sarah Morin, Grant McClearn, Neal McBurnett & Poorvi L. Vora

  2. Department of Computer Science, Wroclaw University of Science and Technology, Wroclaw, Poland

    Filip Zagórski

Authors
  1. Sarah Morin
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  2. Grant McClearn
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  3. Neal McBurnett
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  4. Poorvi L. Vora
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  5. Filip Zagórski
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Corresponding author

Correspondence to Poorvi L. Vora .

Editor information

Editors and Affiliations

  1. University of Michigan–Ann Arbor, Ann Arbor, USA

    Matthew Bernhard

  2. Computing Science and Mathematics, University of Stirling, Stirling, UK

    Andrea Bracciali

  3. Computer Science Department, Indiana University, Bloomington, USA

    L. Jean Camp

  4. Department of Computer Science, Georgetown University, Washington, WA, USA

    Shin'ichiro Matsuo

  5. Western Sydney University, Parramatta, Australia

    Alana Maurushat

  6. Maison du Nombre, University of Luxembourg, Esch-sur-Alzette, Luxembourg

    Peter B. Rønne

  7. Dipartimento di Matematica, University of Trento, Trento, Trento, Italy

    Massimiliano Sala

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Morin, S., McClearn, G., McBurnett, N., Vora, P.L., Zagórski, F. (2020). A Note on Risk-Limiting Bayesian Polling Audits for Two-Candidate Elections. In: Bernhard, M., et al. Financial Cryptography and Data Security. FC 2020. Lecture Notes in Computer Science(), vol 12063. Springer, Cham. https://doi.org/10.1007/978-3-030-54455-3_24

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  • DOI: https://doi.org/10.1007/978-3-030-54455-3_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-54454-6

  • Online ISBN: 978-3-030-54455-3

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