Rozalina Doneva (Karlsruhe Institute of Technology (KIT)), Anne Hennig (Karlsruhe Institute of Technology (KIT)), Peter Mayer (University of Southern Denmark (SDU))

While passwordless authentication methods are on the rise, password-based authentication remains widely used in practice. In search of effective means to promote stronger password choices, we created and evaluated the effectiveness of six interactive password strength calculator designs with respect to usability, emotional affect, password strength, and password length, by conducting an online survey with 89 participants. The results showed that while all six designs increased password strength and length compared to the control group, the differences were not statistically significant. Based on the mean values, fear-appeal nudges yielded results of similar strength to positive-feedback nudges. Still, positive feedback nudges resulted in slightly longer passwords, breaking with the paradigm that only fear appeals effectively support the creation of secure passwords. Furthermore, designs with additional information and guidance yielded longer and stronger passwords than those without, although the differences were not statistically significant. However, designs with additional information guidance exhibited significantly higher usability scores, indicating that providing guidance not only has the potential to enhance password security effectively but also improves usability.

View More Papers

NetCap: Data-Plane Capability-Based Defense Against Token Theft in Network...

Osama Bajaber (Virginia Tech), Bo Ji (Virginia Tech), Peng Gao (Virginia Tech)

Read More

Victim-Centred Abuse Investigations and Defenses for Social Media Platforms

Zaid Hakami (Florida International University and Jazan University), Ashfaq Ali Shafin (Florida International University), Peter J. Clarke (Florida International University), Niki Pissinou (Florida International University), and Bogdan Carbunar (Florida International University)

Read More

How to Effectively Trace Provenance on Windows Endpoint Detection...

Jason Liu (University of Illinois at Urbana-Champaign), Muhammad Adil Inam (University of Illinois at Urbana-Champaign), Akul Goyal (University of Illinois at Urbana-Champaign), Dylen Greenenwald (University of Illinois at Urbana-Champaign), Adam Bates (University of Illinois at Urbana-Champaign), Saurav Chittal (Purdue University)

Read More