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      SOBA: Secrecy-preserving Observable Ballot-level Audit

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          Abstract

          SOBA is an approach to election verification that provides observers with justifiably high confidence that the reported results of an election are consistent with an audit trail ("ballots"), which can be paper or electronic. SOBA combines three ideas: (1) publishing cast vote records (CVRs) separately for each contest, so that anyone can verify that each reported contest outcome is correct, if the CVRs reflect voters' intentions with sufficient accuracy; (2) shrouding a mapping between ballots and the CVRs for those ballots to prevent the loss of privacy that could occur otherwise; (3) assessing the accuracy with which the CVRs reflect voters' intentions for a collection of contests while simultaneously assessing the integrity of the shrouded mapping between ballots and CVRs by comparing randomly selected ballots to the CVRs that purport to represent them. Step (1) is related to work by the Humboldt County Election Transparency Project, but publishing CVRs separately for individual contests rather than images of entire ballots preserves privacy. Step (2) requires a cryptographic commitment from elections officials. Observers participate in step (3), which relies on the "super-simple simultaneous single-ballot risk-limiting audit." Step (3) is designed to reveal relatively few ballots if the shrouded mapping is proper and the CVRs accurately reflect voter intent. But if the reported outcomes of the contests differ from the outcomes that a full hand count would show, step (3) is guaranteed to have a large chance of requiring all the ballots to be counted by hand, thereby limiting the risk that an incorrect outcome will become official and final.

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          Most cited references6

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          Risk-Limiting Postelection Audits: Conservative $P$-Values From Common Probability Inequalities

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            CAST: Canvass Audits by Sampling and Testing

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              Conservative statistical post-election audits

              (2008)
              There are many sources of error in counting votes: the apparent winner might not be the rightful winner. Hand tallies of the votes in a random sample of precincts can be used to test the hypothesis that a full manual recount would find a different outcome. This paper develops a conservative sequential test based on the vote-counting errors found in a hand tally of a simple or stratified random sample of precincts. The procedure includes a natural escalation: If the hypothesis that the apparent outcome is incorrect is not rejected at stage \(s\), more precincts are audited. Eventually, either the hypothesis is rejected--and the apparent outcome is confirmed--or all precincts have been audited and the true outcome is known. The test uses a priori bounds on the overstatement of the margin that could result from error in each precinct. Such bounds can be derived from the reported counts in each precinct and upper bounds on the number of votes cast in each precinct. The test allows errors in different precincts to be treated differently to reflect voting technology or precinct sizes. It is not optimal, but it is conservative: the chance of erroneously confirming the outcome of a contest if a full manual recount would show a different outcome is no larger than the nominal significance level. The approach also gives a conservative \(P\)-value for the hypothesis that a full manual recount would find a different outcome, given the errors found in a fixed size sample. This is illustrated with two contests from November, 2006: the U.S. Senate race in Minnesota and a school board race for the Sausalito Marin City School District in California, a small contest in which voters could vote for up to three candidates.
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                Author and article information

                Journal
                29 May 2011
                2011-07-02
                Article
                1105.5803
                bc3c8610-0823-4a1d-a2a7-00750def3df4

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                stat.AP cs.CR cs.CY

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