Assessing intrusiveness of smartphone apps
Name
871171739-MIT.pdf
Description
Full printable version
Size
8.34 MB
Format
Adobe PDF
Checksum (MD5)
60a874006babed3b9944aaf08aac578b
Author(s)
Zhang, Fan, M. Eng. Massachusetts Institute of Technology
Advisor(s)
Hal Abelson.
Alternative Title
AppWindow : tracking mobile apps tracking you
Date Issued
2012
Publisher
Massachusetts Institute of Technology
Abstract
We tackle the challenge of improving transparency for smartphone apps by focusing on the intrusiveness component of assessing privacy risk. Specifically, we develop a framework for qualitatively assessing and quantitatively measuring the intrusiveness of apps based on their data access behavior. This framework has two essential components: 1) the Privacy Fingerprint, a concise yet holistic visual that captures the data access patterns unique to each app, including which types and under which privacy-relevant usage contexts sensitive data are collected, and 2) an Intrusiveness Score that numerically measures each app's level of intrusiveness, based on real data accesses gathered from empirical testing on about 40 popular Android apps across 4 app categories. Used together, the Privacy Fingerprint and Intrusiveness Score help smartphone users easily and accurately assess the relative intrusiveness of apps during the decision-making process of installing apps. Our study demonstrates that the Intrusiveness Score is especially useful in helping to compare apps that exhibit similar types of data accesses. Another major contribution of the thesis is the identification and quantification of the proportion of accesses that are made while the user is idle. As our preliminary user study will show, this level of idle access activity significantly enhances the profiling potential of apps, increasing the app's intrusiveness. When quantified, idle access activity exerts significant impact on changes in an app's Intrusiveness Score and its relative intrusiveness ranking within a given app category.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 123-125).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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