E-Vote Your Conscience: Perceptions of Coercion and Vote Buying, and the Usability of Fake Credentials in Online Voting
Louis-Henri Merino, Alaleh Azhir, Haoqian Zhang, Simone Colombo, Bernhard Tellenbach, Vero Estrada-Galiñanes, Bryan Ford
Abstract
Online voting is attractive for convenience and accessibility, but is more susceptible to voter coercion and vote buying than in-person voting. One mitigation is to give voters fake voting credentials that they can yield to a coercer. Fake credentials appear identical to real ones, but cast votes that are silently omitted from the final tally. An important unanswered question is how ordinary voters perceive such a mitigation: whether they could understand and use fake credentials, and whether the coercion risks justify the costs of mitigation. We present the first systematic study of these questions, involving 150 diverse individuals in Boston, Massachusetts. All participants "registered" and "voted" in a mock election: 120 were exposed to coercion resistance via fake credentials, the rest forming a control group. Of the 120 participants exposed to fake credentials, 96% understood their use. 53% reported that they would create fake credentials in a real-world voting scenario, given the opportunity. 10% mistakenly voted with a fake credential, however. 22% reported either personal experience with or direct knowledge of coercion or vote-buying incidents. These latter participants rated the coercion-resistant system essentially as trustworthy as in-person voting via hand-marked paper ballots. Of the 150 total participants to use the system, 87% successfully created their credentials without assistance; 83% both successfully created and properly used their credentials. Participants give a System Usability Scale score of 70.4, which is slightly above the industry’s average score of 68. Our findings appear to support the importance of the coercion problem in general, and the promise of fake credentials as a possible mitigation, but user error rates remain an important usability challenge for future work.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers1
Ask how each one uses itBuilds on3
- SoK: Verifiability Notions for E-Voting ProtocolsVéronique Cortier, David Galindo, Ralf Küsters, Johannes Müller et al.S&P 2016 · 125 citations
- Can Voters Detect Malicious Manipulation of Ballot Marking Devices?Matthew Bernhard, Allison McDonald, Henry Meng, Jensen Hwa et al.S&P 2020 · 44 citations
- VoteAgain: A scalable coercion-resistant voting systemWouter Lueks, Iñigo Querejeta-Azurmendi, Carmela TroncosoUSENIX Security 2020
Related papers
- Thwarting Last-Minute Voter CoercionRosario Giustolisi, Maryam Sheikhi Garjan, Carsten SchürmannS&P 2024 · 9 citations
- Why Johnny Checks but Doesn't Alert: Reporting as the Missing Step in Verifiable Internet VotingTobias Hilt, Christian Mack, Benjamin Maximilian Berens, Melanie VolkamerCHI 2026
- Investigating Voter Perceptions of Printed Physical Audit Trails for Online VotingKarola Marky, Nina Gerber, Henry John Krumb, Mohamed Khamis et al.S&P 2024 · 1 citation
- Busting the Paper Ballot: Voting Meets Adversarial Machine LearningKaleel Mahmood, Caleb Manicke, Ethan Rathbun, Aayushi Verma et al.CCS 2025
- Designing Effective Digital Literacy Interventions for Boosting Deepfake DiscernmentDominique Geissler, Claire Robertson, Stefan FeuerriegelCHI 2026 · 3 citations
