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Is Bigger Better? Comparing User-Generated Passwords on 3x3 vs. 4x4 Grid Sizes for Android's Pattern Unlock

Published: 07 December 2015 Publication History

Abstract

Android's graphical authentication mechanism requires users to unlock their devices by "drawing" a pattern that connects a sequence of contact points arranged in a 3x3 grid. Prior studies demonstrated that human-generated 3x3 patterns are weak (CCS'13); large portions can be trivially guessed with sufficient training. An obvious solution would be to increase the grid size to increase the complexity of chosen patterns. In this paper we ask the question: Does increasing the grid size increase the security of human-generated patterns? We conducted two large studies to answer this question, and our analysis shows that for both 3x3 and 4x4 patterns, there is a high incidence of repeated patterns and symmetric pairs (patterns that derive from others based on a sequence of flips and rotations), and many 4x4 patterns are expanded versions of 3x3 patterns. Leveraging this information, we developed an advanced guessing algorithm and used it to quantified the strength of the patterns using the partial guessing entropy. We find that guessing the first 20% (G0.2) of patterns for both 3x3 and 4x4 can be done as efficiently as guessing a random 2-digit PIN. While guessing larger portions of 4x4 patterns (G0.5) requires 2-bits more entropy than guessing the same ratio of 3x3 patterns, it remains on the order of cracking random 3-digit PINs. Of the patterns tested, our guessing algorithm successful cracks 15% of 3x3 patterns within 20 guesses (a typical phone lockout) and 19% of 4x4 patterns within 20 guesses; however, after 50,000 guesses, we correctly guess 95.9% of 3x3 patterns but only 66.7% of 4x4 patterns. While there may be some benefit to expanding the grid size to 4x4, we argue the majority of patterns chosen by users will remain trivially guessable and insecure against broad guessing attacks.

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ACSAC '15: Proceedings of the 31st Annual Computer Security Applications Conference
December 2015
489 pages
ISBN:9781450336826
DOI:10.1145/2818000
Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of the United States government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Published: 07 December 2015

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  • (2024)FingerPattern: Securing Pattern Lock via Fingerprint-Dependent Friction SoundIEEE Transactions on Mobile Computing10.1109/TMC.2023.333814823:6(7210-7224)Online publication date: Jun-2024
  • (2024)A Random and Unselectable Graphic Password Scheme2024 IEEE 7th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)10.1109/IAEAC59436.2024.10503722(41-46)Online publication date: 15-Mar-2024
  • (2023)“Someone Definitely Used 0000”: Strategies, Performance, and User Perception of Novice Smartphone-Unlock PIN-GuessersProceedings of the 2023 European Symposium on Usable Security10.1145/3617072.3617113(158-174)Online publication date: 16-Oct-2023
  • (2023)Better the Devil You Know: Using Lost-Smartphone Scenarios to Explore user Perceptions of Unauthorised AccessProceedings of the 2023 European Symposium on Usable Security10.1145/3617072.3617104(86-96)Online publication date: 16-Oct-2023
  • (2023)GestureMeter: Design and Evaluation of a Gesture Password Strength MeterProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581397(1-19)Online publication date: 19-Apr-2023
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