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Title: VoteXX: Extreme Coercion Resistance
We solve a long-standing challenge to the integrity of votes cast without the supervision of a voting booth: ``improper influence,'' which we define as any combination of vote buying and voter coercion. In comparison with previous proposals, our system is the first in the literature to protect against a strong adversary who learns all of the voter's keys---we call this property ``extreme coercion resistance.'' Our approach allows each voter, or their trusted agents (which we call ``hedgehogs''), to ``nullify'' (effectively cancel) their vote in a way that is unstoppable and irrevocable, and such that the nullification action is forever unattributable to that voter or their hedgehog(s). We demonstrate the security of VoteXX in the {universal composability} model. Additionally we provide concrete implementations of sub-protocols---including inalienable authentication, decentralized bulletin boards, and anonymous communication channels---that are usually left as abstract assumptions in the literature. As in many other coercion-resistant systems, voters are authorized to vote with public-private keys. Each voter registers their public keys with the Election Authority (EA) in a way that convinces the EA that the voter has complete knowledge of their private keys. Voters concerned about losing their private keys can themselves, or by delegating to one or more hedgehog(s), monitor the bulletin board for malicious ballots cast with their keys, and can act to nullify these ballots in a privacy-preserving manner with zero-knowledge proofs. In comparison with previous proposals, our system makes fewer assumptions and protects against a stronger adversary. For example, votexx makes none of the following assumptions made by previous systems: the voter must complete registration before being coerced; the election will not close before the voter can cast a ballot after coercion; the voter needs to generate a fake password to evade coercion; and the voter knows an honest Election Authority official.  more » « less
Award ID(s):
1753681
NSF-PAR ID:
10474435
Author(s) / Creator(s):
Publisher / Repository:
ACM
Date Published:
Journal Name:
ACM CCS (submitted)
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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