Verifiable Postal Voting

  • Josh Benaloh
  • Peter Y. A. Ryan
  • Vanessa Teague
Conference paper

DOI: 10.1007/978-3-642-41717-7_8

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8263)
Cite this paper as:
Benaloh J., Ryan P.Y.A., Teague V. (2013) Verifiable Postal Voting. In: Christianson B., Malcolm J., Stajano F., Anderson J., Bonneau J. (eds) Security Protocols XXI. Security Protocols 2013. Lecture Notes in Computer Science, vol 8263. Springer, Berlin, Heidelberg

Abstract

This proposal aims to combine the best properties of paper-based and end-to-end verifiable remote voting systems. Ballots are delivered electronically to voters, who return their votes on paper together with some cryptographic information that allows them to verify later that their votes were correctly included and counted.

We emphasise the ease of the voter’s experience, which is not much harder than basic electronic delivery and postal returns. A typical voter needs only to perform a simple check that the human-readable printout reflects the intended vote. The only extra work is adding some cryptographic information into the same envelope as the human-readable vote.

The proposed scheme is not strictly end-to-end verifiable, because it depends on procedural assumptions at the point where the ballots are received. These procedures should be public and could be enforced by a group of observers, but are not publicly verifiable afterwards by observers who were absent at the time.

Keywords

electronic voting verifiability postal voting vote by mail end-to-end verifiable voting 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Josh Benaloh
    • 1
  • Peter Y. A. Ryan
    • 2
  • Vanessa Teague
    • 3
  1. 1.Microsoft ResearchRedmondUSA
  2. 2.University of LuxembourgLuxembourg
  3. 3.Department of Computing and Information SystemsUniversity of MelbourneAustralia

Personalised recommendations