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Does my password go up to eleven?: the impact of password meters on password selection

Egelman, Serge, Sotirakopoulos, Andreas, Muslukhov, Ildar, Beznosov, Konstantin, Herley, Cormac·2013·Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Abstract

Password meters tell users whether their passwords are "weak" or "strong." We performed a laboratory experiment to examine whether these meters influenced users' password selections when they were forced to change their real passwords, and when they were not told that their passwords were the subject of a study. We observed that the presence of meters yielded significantly stronger passwords. We performed a followup field experiment to test a different scenario: creating a password for an unimportant account. In this scenario, we found that the meters made no observable difference: participants simply reused weak passwords that they used to protect similar low-risk accounts. We conclude that meters result in stronger passwords when users are forced to change existing passwords on "important" accounts and that individual meter design decisions likely have a marginal impact.

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Metadata

Authors
Egelman, S., Sotirakopoulos, A., Muslukhov, I., Beznosov, K., & Herley, C.
Venue
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2013-04-27
Pages
2379-2388
OpenAlex
W2134080857
Cited by
197
References
0
FWCI
18.30
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Does my password go up to eleven?: the impact of password meters on password selection. https://app.cochat.ai/papers/10.1145/2470654.2481329
The paper
Egelman, S., Sotirakopoulos, A., Muslukhov, I., Beznosov, K., & Herley, C. (2013). Does my password go up to eleven?: the impact of password meters on password selection. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/2470654.2481329

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.