Akash Lohani

Graduation Semester and Year

2020

Language

English

Document Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science and Engineering

First Advisor

Ming Li

Abstract

Nowadays, smartwatches have become one of the most common wearable gadgets as they are small and portable. As more and more personal information is managed and processed inside smartwatches, it is important to have a secure user authentication scheme in place. There have been many successful authentication schemes for a smartphones such as Password/PIN, bio-metric approach(e.g. fingerprint, face recognition), etc directly used on smartwatches. However, these approaches are not quite suitable for smartwatches due to its constraints in size and limited computation power. To address this issue, we propose TaPIN that allows users to authenticate themselves by playing out the rhythmical tap with their thumb and forefinger. TaPIN is a two-factor user authentication scheme that incorporates not only the user's knowledge-based rhythmical tapping pattern but also the corresponding vibration bio-metric exhibited during finger tapping. To validate the scheme, we built a proof-of-concept prototype, conducted extensive experiments with human subjects, and demonstrated that TaPIN achieves high accuracy and is resistant to various types of attacks. More importantly it is convenient to perform with one hand.

Keywords

Security, Privacy, Mobile Sensing

Disciplines

Computer Sciences | Physical Sciences and Mathematics

Comments

Degree granted by The University of Texas at Arlington

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