Authenticating a Known User Through Behavioral Biometrics Using a Smartphone Accelerometer
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Authors
Jones, Patrick
Subjects
smartphone
authentication
behavioral biometrics
accelerometer
Android
authentication
behavioral biometrics
accelerometer
Android
Advisors
McEachen, John C.
Thulasiraman, Preetha
Date of Issue
2017-12
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
This thesis investigates the feasibility of authenticating a user through a behavioral biometric signature from smartphone accelerometer data. Using a Samsung Galaxy S7, acceleration in relation to the necessary equilibrium, postural state for a subject to orient a smartphone in order to read a headline article was measured and recorded by the MATLAB Mobile application. Twenty subjects—1 known and 19 unknown—were used in the creation of a MATLAB machine-learning classifier. The classifier accurately distinguished an unknown subject from the known subject. Recommendations for future work include repeating the experiment with the latest smartphone devices as available, incorporating different sensors available to the “MATLAB Mobile App,” and introducing noise to spoof the known user.
Type
Thesis
Description
Series/Report No
Department
Electrical and Computer Engineering (ECE)
Organization
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.