Orientation Based Accelerometer Analysis (OBAA) for Mobile Gestures: Memorable Authentication
Abstract
Mobile authentication today primarily relies on
Personal Identification Numbers (PINs). For PINs to be secure
from the majority of malicious users, it must contain a high
number of digits and be entropic. Human memory generally
struggles when it attempts to recall highly entropic numeric
codes. Gesture-based authentication using Quick Reference (QR)
codes, and internally analyzed accelerometer data from mobile
devices, allow for sustaining a more user-friendly, memorable,
and low expense alternative to PINs. This paper presents a
technique for users to capture movements of their mobile device
by analyzing the orientation of devices and the speed at which
these orientations transition via accelerometer data. These
motions are described as the user’s gesture. Gestures can be used
to identify a user, while QR codes can be used to indicate a
specific machine a user can attempt to authenticate with. A user
study was performed and showed gesture-based authentication
results in a more user preferred, entropic and memorable
authentication system in comparison to similar applications.
Keywords
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