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Proceedings of the ACM on Human-Computer Interaction
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
DBLP
Article . 2024
Data sources: DBLP
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Priming through Persuasion: Towards Secure Password Behavior

Authors: Rizu Paudel; Mahdi Nasrullah Al-Ameen;

Priming through Persuasion: Towards Secure Password Behavior

Abstract

Users tend to create weak passwords even for the important accounts. The prior research shed light on user's insecure password behavior, and why the interventions, including requirement specification (e.g., password composition policies) and feedback systems (e.g., password meters) fail in practice. To this end, we propose and evaluate the concept: priming-through-persuasion in the realm of secure password creation. In particular, we created visual designs, aimed at priming users about the repercussions of weak passwords before their password creation. We base our designs on two forms of persuasion methods: pathos and logos. Pathos appeals to people's emotion in order to persuade them towards an expected behavior, where logos-based rhetoric appeals to a person's sense of reason. We conducted a lab study including participatory design and semi-structured interview with 20 participants. We updated our designs in an iterative manner based on the feedback from our participants in the lab study. To evaluate our updated designs, we conducted a between-subject online study with 131 participants over Amazon Mechanical Turk. Our study provides insight into how the use of persuasion techniques contributed to user attachment and engagement with the design, as well as the comprehension of the conveyed message about password vulnerabilities. Our findings lead to the guideline for future research on leveraging the priming-through-persuasion to complement the existing techniques in encouraging users towards secure behavior.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Top 10%
Top 10%
hybrid