zxcvbn: Low-Budget Password Strength Estimation
Author(s): Daniel Lowe Wheeler

Date: August 10 2016
Publication: Proceedings of the 25st USENIX Security Symposium (SEC'16)
Publisher: USENIX
Source 1: https://www.usenix.org/system/files/conference/usenixsecurity16/sec16_paper_wheeler.pdf

Abstract or Summary:
For over 30 years, password requirements and feedback have largely remained a product of LUDS: counts of lower- and uppercase letters, digits and symbols. LUDS remains ubiquitous despite being a conclusively burdensome and ineffective security practice.

zxcvbn is an alternative password strength estimator that is small, fast, and crucially no harder than LUDS to adopt. Using leaked passwords, we compare its estimations to the best of four modern guessing attacks and show it to be accurate and conservative at low magnitudes, suitable for mitigating online attacks. We find 1.5 MB of compressed storage is sufficient to accurately estimate the best-known guessing attacks up to 105 guesses, or 104 and 103 guesses, respectively, given 245 kB and 29 kB. zxcvbn can be adopted with 4 lines of code and downloaded in seconds. It runs in milliseconds and works as-is on web, iOS and Android.

PasswordResearch.com Note: Video of presentation: https://www.usenix.org/conference/usenixsecurity16/technical-sessions/presentation/wheeler

Do you have additional information to contribute regarding this research paper? If so, please email siteupdates@passwordresearch.com with the details.

<-- Back to Authentication Research Paper Index

[Home] [About Us] [News] [Research]

Copyright © 2016 PasswordResearch.com