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ACT-R Modeling of Password Entry Errors

Published

Author(s)

Kristen Greene, Franklin Tamborello

Abstract

Validated predictive models of human error for password-related tasks could better inform password requirements for both government and civilian systems. Here, we build upon prior modeling work focused on disentangling the source of password entry errors—recall errors versus motor execution errors—reported in behavioral studies. In the current work, we significantly modify the password rehearsal model previously reported by Greene and Tamborello (2015). The modified model is now ready to test with recent ACT-R typing modifications necessary for modeling password typing, i.e., the ability for ACT-R to type capital letters and symbols, and to make motor errors while doing so (Greene & Tamborello, 2015).
Proceedings Title
Proceedings of the 24th Conference on Behavior Representation in Modeling and Simulation
Conference Dates
March 31-April 3, 2015
Conference Location
Washington, DC
Conference Title
24th Conference on Behavior Representation in Modeling and Simulation (BRiMS 2015)

Keywords

ACT-R, Human Error, Memory, Typing

Citation

Greene, K. and Tamborello, F. (2015), ACT-R Modeling of Password Entry Errors, Proceedings of the 24th Conference on Behavior Representation in Modeling and Simulation, Washington, DC (Accessed July 19, 2024)

Issues

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Created April 2, 2015, Updated February 19, 2017