ACT-R Modeling of Password Entry Errors

Published

April 2, 2015

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)

Pub Type

Conferences

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 April 16, 2024)