Wenqiang Jin

Graduation Semester and Year

2021

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Computer Science

Department

Computer Science and Engineering

First Advisor

Ming Li

Abstract

The exploding growth of mobile devices like smartphones and wearables has envisioned various applications, which are developed to collect a wide spectrum of data using on-board device sensors and process them to serve peoples' life in all kinds of scenarios. Noticing the sensing capabilities of current mobile device are limited to its on-board sensors' default functionalities. We study the mechanism designs that extend the mobile device's sensing capabilities to perform new sensing tasks other than its defaults. In this thesis, we investigate the mobile systems' security issues and develop new applications by exploring the device's sensing capabilities. Our contributions are mainly threefold. First, we address the challenges of device pairing between wearables by leveraging its on-board transceivers. Specifically, we use wearables' transceivers to harvest ambient radio frequency (RF) noise from open-air and turn them into the ingredients for the secret key establishment. Second, we introduce a novel side-channel attack to infer user's secret PINs typed on mobile device's touchscreens by eavesdropping and analyzing its electromagnetic emanations. In particular, we observe that the finger movements on the touchscreen leads to time-variant coupling between the human body and the touchscreen. Consequently, it results variations of touchscreen's electromagnetic emanations, which can be captured by electrical potential sensors and leveraged to reconstruct the finger movement traces on the keypad during its typing process. Third, we develop an acoustic ranging application that assists pedestrians with vision impairment to across uncontrolled streets. The application leverages smartphone's microphones to sense motion status of oncoming vehicles. Based on the measurement results, it then detects the potential collisions and alert the pedestrians ahead.

Keywords

Mobile systems, Secure pairing, Keystroke inferences, Acoustic ranging

Disciplines

Computer Sciences | Physical Sciences and Mathematics

Comments

Degree granted by The University of Texas at Arlington

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