Paper Info
Title
Why Are They Collecting My Data?: Inferring the Purposes of Network Traffic in Mobile Apps.
Abstract
Many smartphone apps collect potentially sensitive personal data and send it to cloud servers. However, most mobile users have a poor understanding of why their data is being collected. We present MobiPurpose, a novel technique that can take a network request made by an Android app and then classify the data collection purposes, as one step towards making it possible to explain to non-experts the data disclosure contexts. Our purpose inference works by leveraging two observations: 1) developer naming conventions (e.g., URL paths) of ten offer hints as to data collection purposes, and 2) external knowledge, such as app metadata and information about the domain name, are meaningful cues that can be used to infer the behavior of different traffic requests. MobiPurpose parses each traffic request body into key-value pairs, and infers the data type and data collection purpose of each key-value pair using a combination of supervised learning and text pattern bootstrapping. We evaluated MobiPurpose's effectiveness using a dataset cross-labeled by ten human experts. Our results show that MobiPurpose can predict the data collection purpose with an average precision of 84% (among 19 unique categories).
Year
DOI
Venue
2018
10.1145/3287051
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Keywords
DocType
Volume
Contextual Integrity,Mobile Privacy,Privacy in Context,Purposes of Data Collection
Journal
2
Issue
ISSN
Citations 
4
2474-9567
2
PageRank 
References 
Authors
0.36
0
8
Name
Order
Citations
PageRank
Haojian Jin14610.08
Minyi Liu220.36
Kevan Dodhia320.36
Yuanchun Li4165.70
Gaurav Srivastava534349.08
Matt Fredrikson697248.56
Yuvraj Agarwal71327102.62
Jason Hong86706518.75