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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
    • George Mason University

    Research output: Contribution to journal › Conference article › peer-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 2024 → 13 Sep 2024

    Keywords

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

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