Using a Blocklist to Improve the Security of User Selection of Android Patterns

Collins W. Munyendo*, Miles Grant*, Philipp Markert, Timothy J. Forman§, Adam J. Aviv*

*The George Washington University, Ruhr University Bochum, §United States Navy


Android patterns remain a popular method for unlocking smartphones, despite evidence suggesting that many users choose easily guessable patterns. In this paper, we explore the usage of blocklists to improve the security of user-chosen patterns by disallowing common patterns, a feature currently unavailable on Android but used by Apple during PIN selection. In a user study run on participants' smartphones (n=1006), we tested 5 different blocklist sizes and compared them to a control treatment. We find that even the smallest blocklist (12 patterns) had benefits, reducing a simulated attacker's success rate after 30 guesses from 24% to 20%. The largest blocklist (581 patterns) reduced the percentage of correctly guessed patterns after 30 attempts down to only 2%. In terms of usability, blocklists had limited negative impact on short-term recall rates and entry times, with reported SUS values indicating reasonable usability when selecting patterns in the presence of a blocklist. Based on our simulated attacker performance results for different blocklist sizes, we recommend blocking 100 patterns for a good balance between usability and security.

Study Data

We share the dataset of user-chosen Android Patterns with other research institutions upon request.

Technical Paper

Our work appeared at the 17th Symposium on Usable Privacy and Security.
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