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Election Security Is Harder Than You Think

dc.contributor.authorBernhard, Matthew
dc.date.accessioned2020-10-04T23:38:14Z
dc.date.availableNO_RESTRICTION
dc.date.available2020-10-04T23:38:14Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/2027.42/163272
dc.description.abstractRecent years have seen the rise of nation-state interference in elections across the globe, making the ever-present need for more secure elections all the more dire. While certain common-sense approaches have been a typical response in the past, e.g. ``don't connect voting machines to the Internet'' and ``use a voting system with a paper trail'', known-good solutions to improving election security have languished in relative obscurity for decades. These techniques are only now finally being implemented at scale, and that implementation has brought the intricacies of sophisticated approaches to election security into full relief. This dissertation argues that while approaches to improve election security like paper ballots and post-election audits seem straightforward, in reality there are significant practical barriers to sufficient implementation. Overcoming these barriers is a necessary condition for an election to be secure, and while doing so is possible, it requires significant refinement of existing techniques. In order to better understand how election security technology can be improved, I first develop what it means for an election to be secure. I then delve into experimental results regarding voter-verified paper, discussing the challenges presented by paper ballots as well as some strategies to improve the security they can deliver. I examine the post-election audit ecosystem and propose a manifest improvement to audit workload analysis through parallelization. Finally, I show that even when all of these conditions are met (as in a vote-by-mail scenario), there are still wrinkles that must be addressed for an election to be truly secure.
dc.language.isoen_US
dc.subjectElection Security
dc.titleElection Security Is Harder Than You Think
dc.typeThesis
dc.description.thesisdegreenamePhDen_US
dc.description.thesisdegreedisciplineComputer Science & Engineering
dc.description.thesisdegreegrantorUniversity of Michigan, Horace H. Rackham School of Graduate Studies
dc.contributor.committeememberHalderman, J Alex
dc.contributor.committeememberMebane Jr, Walter R
dc.contributor.committeememberBanovic, Nikola
dc.contributor.committeememberHoneyman, Peter
dc.contributor.committeememberRivest, Ronald
dc.subject.hlbsecondlevelComputer Science
dc.subject.hlbtoplevelEngineering
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/163272/1/matber_1.pdfen_US
dc.identifier.orcid0000-0002-2700-8921
dc.identifier.name-orcidBernhard, Matthew; 0000-0002-2700-8921en_US
dc.owningcollnameDissertations and Theses (Ph.D. and Master's)


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