Improving the Security of Android Unlock Patterns Using New Iterations of the Standard Pattern Lock
Abstract
Android mobile devices use a unique method of authentication in the form of a single-stroke graphical pattern on a 3x3 grid that a user is required to create and recall. In this research project, we are going to explore improved iterations of this Android Pattern Lock in the pursuit of guiding users towards creating more secure patterns. Within the past five years, Mobile Authentication methods have continually progressed towards creating a more secure means to safeguard a mobile device. Such methods now include biometric identification, system assisted password guidance via blacklists, and longer minimum passcode lengths. While many methods have progressed, the standard authentication interface for Android devices remains similar in comparison to its initial model. In this work, we sought to explore the effects of changing the existing Android pattern lock interface to an interface we deemed the Double Pattern. We examined the methodologies by which users chose their Double Patterns using our new interface, specifically metrics related to the complexity of the patterns created, pattern frequency within each treatment population, usability aspects of the interface itself, security strength of our interface, and perceived security strength related to existing authentication methods. Ultimately, we found that our Double Pattern had a significant increase in security related to lower partial guessing entropy and lower susceptibility to simulated guessing attacks, due to the low occurrence rate of each Double Pattern. Equally important, participants perceived the Double Pattern as a more secure interface than the original interface, specifically within our users who previously utilized Android unlock patterns. We are confident based on these results that the Double Pattern could be feasibly implemented as a progression of the original Android unlock pattern interface.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 06, 2020
- Accession Number
- AD1136700
Entities
People
- Timothy J. Forman
Organizations
- United States Naval Academy