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Enabling More Meaningful Post-Election Investigations



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Enabling More Meaningful Post Election Investigations by Arel Lee Cordero A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Electrical Engineeing and Computer Sciences in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA BERKELEY Committee in charge Professor David Wagner Chair Professor Jitendra Malik Professor Deirdre Mulligan Fall 2010 Enabling More Meaningful Post Election Investigations Copyright c 2010 by Arel Lee Cordero Abstract Enabling More Meaningful Post Election Investigations by Arel Lee Cordero Doctor of Philosophy in Electrical Engineeing and Computer Sciences University of California Berkeley Professor David Wagner Chair Post election audits and investigations can produce more transparent trustworthy and secure elections However such investigations are limited in cases by inadequate tools and methods an absence of meaningful evidence and high costs In this dissertation I address these concerns in the following three lines of research First I describe my research on verifiable and transparent random sample selection for post election audits I investigate how counties have typically approached random sample selection and I analyze the implications and limitations of those approaches I propose a sampling method that has since found use in counties across the country Second I describe a novel approach for logging events in direct recording electronic DRE voting systems My approach gives investigators more meaningful evidence about the behavior of DREs on election day In particular I propose to record interactions between the voter and the voting machine such that they can be replayed by investigators while preserving the anonymity of the voter Last I describe a novel process for efficiently verifying elections that use optical scan voting systems My process uses image superposition to let an investigator visualize the content of many ballot images simultaneously while allowing individual



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