Bernoulli Ballot Polling: A Manifest Improvement for Risk-Limiting Audits
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1812.06361.pdf
Description
Submitted version
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448.86 KB
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Adobe PDF
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Author(s)
Ottoboni, Kellie
Bernhard, Matthew
Halderman, J. Alex
Rivest, Ronald L
Stark, Philip B.
Date Issued
March 2020
Journal
Lecture Notes in Computer Science
Publisher
Springer International Publishing
Citation
Ottoboni, Kellie et al. "Bernoulli Ballot Polling: A Manifest Improvement for Risk-Limiting Audits."
FC: International Conference on Financial Cryptography and Data Security, Lecture Notes in Computer Science, 11599, Springer International Publishing, 2020, 226-241. © 2020 International Financial Cryptography Association.
Version
Original manuscript
Abstract
We present a method and software for ballot-polling risk-limiting audits (RLAs) based on Bernoulli sampling: ballots are included in the sample with probability p, independently. Bernoulli sampling has several advantages: (1) it does not require a ballot manifest; (2) it can be conducted independently at different locations, rather than requiring a central authority to select the sample from the whole population of cast ballots or requiring stratified sampling; (3) it can start in polling places on election night, before margins are known. If the reported margins for the 2016 U.S. Presidential election are correct, a Bernoulli ballot-polling audit with a risk limit of 5% and a sampling rate of p0=1% would have had at least a 99% probability of confirming the outcome in 42 states. (The other states were more likely to have needed to examine additional ballots). Logistical and security advantages that auditing in the polling place affords may outweigh the cost of examining more ballots than some other methods might require.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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DOI of Published Version
https://doi.org/10.1007/978-3-030-43725-1_16
