ACSAC22-Five-Word-Passwords

User Perceptions of Five-Word Passwords

Xiaoyuan Wu, Collins W. Munyendo, Eddie Cosic, Genevieve A. Flynn, Olivia Legault, Adam J. Aviv

Overview

This repository contains data and survey technology used for the five-word password study:

• qualitative-analysis/: A single pdf with codebook used to code free-response answers in both parts of the survey.
• quantitative-analysis/: Jupyter notebooks used to analyze quantitative data and generate graphs for the paper.
• survey/: Implementation of the two online surveys ("pre-survey" and "post-survey") that yielded the data for this study.
• survey-data/: Participants' response data from both pre and post-survey.
• clean_small_words.txt: Dictionary containing 1,630 words used for the study.
• 2022-ACSAC-Five-Word-Passwords-Artifact-Appendix.pdf: Appendix describing this artifact including an abstract of the artifact, a check-list, links to related folders of this repository and the codebook used in the qualitative analysis.

qualitative-analysis

See the qualitative-analysis' README for details on contents of the folder.

quantitative-analysis

See the quantitative-analysis' README for details on the contents of the folder.

Instructions for Environment Setup

• The simplest way to use Jupyter Notebook is to install Anaconda, packages used for this study (pandas and matplotlib) came pre-installed with Anaconda.
• To install pandas and matplotlib manually, please follow the instructions below:
  • pandas: https://pandas.pydata.org/docs/getting_started/install.html
  • matplotlib: https://matplotlib.org/stable/users/installing/index.html

survey

See the online survey's README for instructions on how to run a local instance of the pre-survey and post-survey.

survey-data

See the survey data's README for details on the collection of structured survey responses.