Using Unrestricted Mobile Sensors to Infer Tapped and Traced User Inputs

<p>As of January 2014, 58% of Americans over the age of 18 own a smart phone. Of these smart phones, Android devices provide some security by requiring that third-party application developers declare to users which components and features their applications will access. However, many of the real-time environmental sensors on devices are exempt from this requirement. We evaluate the possibility of exploiting this freedom to discretely use these sensors and expand on previous work by developing an application that can use the gyroscope and accelerometer to interpret what the user has written, even of trace input is used. Trace input is an option available on Samsung's default keyboard as well as in many popular third-party keyboard applications, such as Swype, SwiftKey, TouchPal, and GO Keyboard. "Tracing" an input involves the user dragging from the first letter of the intended word to the last letter without lifting his or her finger. The inclusion of trace input in a key logger application increases the amount of personal information that can be captured since users may choose to use the time saving trace-based input as opposed to the traditional tapping-based input. In this work, we attempt to interpret user input using accelerometer and gyroscope data given single letter tap and full word trace inputs.</p>

Name thesis:degree_name

Computer Science - Applied Computing Track

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

TSYS School of Computer Science

Year dc:date.available

2015

Author dc:creator

• Nguyen, Trang Duyen

Contributors dc:contributor

• Dr. Radhouane Chouchane
• Dr. Yesem Peker
• Dr. Charles Turnitsa

• Mobile Malware
• Key Logger
• Mobile Security
• Spyware
• Motion Sensors
• Android
• Computer Engineering
• Computer Sciences

Language dc:language

English

Repository record dc:identifier

https://csuepress.columbusstate.edu/theses_dissertations/178

OAI identifier oai:identifier

oai:csuepress.columbusstate.edu:theses_dissertations-1178