Usage of an AI-Based Password Tool: Impacts of Security Fatigue, Age, and Individual Differences

Gerald Matthews, Giuseppe Ateniese, Daniel Barbará, Shawn C. Thayer, Nicholas C. Leskovec

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

Effective usage of AI-powered cybersecurity tools may be reduced by users’ tendencies to minimize effort, especially when they are fatigued. The current study identified multiple factors impacting user interaction with DeepPasswd, a tool utilizing deep learning to enhance password strength. Data were obtained from a demanding but monotonous simulated work task requiring regular password updating. Younger users were less likely than older ones to use the tool. Individual differences in anxiety, trust and fatigue were associated with frequency of password tweaks while using the tool, taken as index of engagement. Data on work task performance suggested users vary in their willingness to apply effort. Mitigation of tool neglect and security fatigue requires greater understanding of how users tradeoff effort against enhanced security.

Original languageEnglish
Pages (from-to)236-242
Number of pages7
JournalProceedings of the Human Factors and Ergonomics Society
Volume68
Issue number1
DOIs
StatePublished - 2024
Event68th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2024 - Phoenix, United States
Duration: 9 Sep 202413 Sep 2024

Keywords

  • artificial intelligence
  • cybersecurity
  • decision making
  • fatigue
  • passwords
  • trust

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