Original paper

Augmenting Password Strength Meter Design Using the Elaboration Likelihood Model: Evidence from Randomized Experiments

Volume: 34, Issue: 1, Pages: 157 - 177
Published: Mar 1, 2023
Abstract
In this research, we study an effective method to encourage users to generate stronger passwords. Specifically, we propose a novel design of password strength meters that incorporates contextual information to help users digest the message generated by the password strength meter. We evaluate our design by leveraging three independent and complementary methods: a survey-based experiment using students to evaluate the saliency of our conceptual...
Paper Details
Title
Augmenting Password Strength Meter Design Using the Elaboration Likelihood Model: Evidence from Randomized Experiments
Published Date
Mar 1, 2023
Volume
34
Issue
1
Pages
157 - 177
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.