Demo Data from EDBT 2026 / reviewers in the wild / expert
Jensen Hwa
dblp:272/8306
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Usability and user experience research · 100% | |
| Network and information security
1 paper |
Cryptographic protocols and secure computation · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Usability and user experience research
security usability |
0.4 | 1 | 2020 | Can Voters Detect Malicious Manipulation of Ballot Marking Devices? · SP 2020 |
Cryptographic protocols and secure computation › electronic voting › verifiable voting
voter verification |
0.4 | 1 | 2020 | Can Voters Detect Malicious Manipulation of Ballot Marking Devices? · SP 2020 |
Methods — techniques the papers use, named apart from their topics
user study · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Can Voters Detect Malicious Manipulation of Ballot Marking Devices?abstractBallot marking devices (BMDs) allow voters to select candidates on a computer kiosk, which prints a paper ballot that the voter can review before inserting it into a scanner to be tabulated. Unlike paperless voting machines, BMDs provide voters an opportunity to verify an auditable physical record of their choices, and a growing number of U.S. jurisdictions are adopting them for all voters. However, the security of BMDs depends on how reliably voters notice and correct any adversarially induced errors on their printed ballots. In order to measure voters' error detection abilities, we conducted a large study (N = 241) in a realistic polling place setting using real voting machines that we modified to introduce an error into each printout. Without intervention, only 40% of participants reviewed their printed ballots at all, and only 6.6% told a poll worker something was wrong. We also find that carefully designed interventions can improve verification performance. Verbally instructing voters to review the printouts and providing a written slate of candidates for whom to vote both significantly increased review and reporting rates-although the improvements may not be large enough to provide strong security in close elections, especially when BMDs are used by all voters. Based on these findings, we make several evidence-based recommendations to help better defend BMD-based elections. Matthew Bernhard, Allison McDonald, Henry Meng, Jensen Hwa, Nakul Bajaj, Kevin Chang 0004, J. Alex Halderman |
SP | 4 |