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NIST Authors in Bold

Displaying 1 - 25 of 126

Workshop Summary Report for ConnectCon 2024: "Minding the Gaps in Human-Centered Cybersecurity"

April 7, 2025
Author(s)
Julie Haney, Matthew Canham, Mike Elkins, Lisa Flynn, Matthew Gordin, Victoria Granova, Wenjing Huang, Jody Jacobs, Greg Moody, Ann Rangarajan, Michael Ross, Robert Thomson, Joe Uchill
In August 2024, the National Institute of Standards and Technology (NIST) co-sponsored ConnectCon, an interactive workshop that facilitated meaningful conversations and connections between researchers and practitioners on the topic of human-centered

Designing Usable Audio for Voting Systems: Best Practices and a Test Approach

January 31, 2025
Author(s)
Lynn Baumeister, Whitney Quesenbery, Sharon J. Laskowski
Voting systems must support multiple interaction modes: presenting information both visually and auditorily, accepting navigation and selections from both screen touches and key presses on a tactile controller. The best practices outlined in this document

Reflection of its Creators: Qualitative Analysis of General Public and Expert Perceptions of Artificial Intelligence

October 16, 2024
Author(s)
Theodore Jensen, Mary Frances Theofanos, Kristen K. Greene, Olivia Williams, Kurtis Goad, Janet Bih Fofang
The increasing prevalence of artificial intelligence (AI) will likely lead to new interactions and impacts for the general public. An understanding of people's perceptions of AI can be leveraged to design and deploy AI systems toward human needs and values

A Review of the Literature on Voter Verification and Ballot Review

July 8, 2024
Author(s)
Whitney Quesenbery, Suzanne Chapman, Christopher Patten, Roberto Spreggiaro, Shanee Dawkins
One of the major issues for voting systems today is whether they provide voters with a meaningful opportunity to verify their ballot before casting it. This opportunity is important in helping them vote their intent by catching errors or omissions made

How Voters Review and Verify Ballots

July 8, 2024
Author(s)
Suzanne Chapman, Lynn Baumeister, Whitney Quesenbery, Shanee Dawkins
Qualitative research to gain deeper insights about how voters mark, review, verify, and cast their ballots. Conducted as part of the work to update the human factors—accessibility, privacy, and usability—requirements in federal voting system standards and

Mathematical Entities: Corpora and Benchmarks

May 20, 2024
Author(s)
Jacob Collard, Valeria de Paiva, Eswaran Subrahmanian
Mathematics is a highly specialized domain with its own unique set of challenges. Despite this, there has been relatively little research on natural language processing for mathematical texts, and there are few mathematical language resources aimed at NLP

Preliminary Study of Mixed Reality Interfaces for Collaborative Robot Programming of a Manufacturing Assembly Task Board

March 9, 2024
Author(s)
Medhavi Kamran, Snehesh Shrestha, Arnav Juneja, Shelly Bagchi, Jeremy Marvel, Megan Zimmerman, Vinh Nguyen
Collaborative robot tasks in manufacturing often involve manually placing and recording the robot in various positions throughout the intended task. However, existing methods for programming robot have been shown to cause physical strain and confusion for

NIST Phish Scale User Guide

November 15, 2023
Author(s)
Shanee Dawkins, Jody Jacobs
The phishing cyber threat exploits vulnerabilities in the U.S. and around the world across private and public sectors. Embedded phishing awareness training programs, where simulated phishing emails are sent to employees, are designed to prepare employees

Can you Spot a Phish?

September 26, 2023
Author(s)
Jody Jacobs, Shanee Dawkins
This talk will cover findings from over 4 years of NIST phishing training data, highlighting user context as the key to phishing susceptibility. We will discuss the NIST Phish Scale, our research on why users click, and how it can help users spot a phish.

Phishing for User Context: Understanding the NIST Phish Scale

August 23, 2023
Author(s)
Shanee Dawkins, Jody Jacobs
The NIST Phish Scale is a method for measuring human phishing detection difficulty, providing a metric – a phishing email detection difficulty rating – for phishing training implementers to gain a better understanding of the variability in click rates
Displaying 1 - 25 of 126
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