Forgetting of Passwords: Ecological Theory and Data


Xianyi Gao, Yulong Yang, Can Liu, Christos Mitropoulos, and Janne Lindqvist, Rutgers University; Antti Oulasvirta, Aalto University


It is well known that text-based passwords are hard to remember and that users prefer simple (and non-secure) passwords. However, despite extensive research on the topic, no principled account exists for explaining when a password will be forgotten. This paper contributes new data and a set of analyses building on the ecological theory of memory and forgetting. We propose that human memory naturally adapts according to an estimate of how often a password will be needed, such that often used, important passwords are less likely to be forgotten. We derive models for login duration and odds of recall as a function of rate of use and number of uses thus far. The models achieved a root-mean-square error (RMSE) of 1.8 seconds for login duration and 0.09 for recall odds for data collected in a month-long field experiment where frequency of password use was controlled. The theory and data shed new light on password management, account usage, password security and memorability.

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@inproceedings {217640,
author = {Xianyi Gao and Yulong Yang and Can Liu and Christos Mitropoulos and Janne Lindqvist and Antti Oulasvirta},
title = {Forgetting of Passwords: Ecological Theory and Data},
booktitle = {27th {USENIX} Security Symposium ({USENIX} Security 18)},
year = {2018},
isbn = {978-1-931971-46-1},
address = {Baltimore, MD},
pages = {221--238},
url = {},
publisher = {{USENIX} Association},