Paper Info
Title
How does misconfiguration of analytic services compromise mobile privacy?
Abstract
ABSTRACTMobile application (app) developers commonly utilize analytic services to analyze their app users' behavior to support debugging, improve service quality, and facilitate advertising. Anonymization and aggregation can reduce the sensitivity of such behavioral data, therefore analytic services often encourage the use of such protections. However, these protections are not directly enforced so it is possible for developers to misconfigure the analytic services and expose personal information, which may cause greater privacy risks. Since people use apps in many aspects of their daily lives, such misconfigurations may lead to the leaking of sensitive personal information such as a users' real-time location, health data, or dating preferences. To study this issue and identify potential privacy risks due to such misconfigurations, we developed a semi-automated approach, Privacy-Aware Analytics Misconfiguration Detector (PAMDroid), which enables our empirical study on mis-configurations of analytic services. This paper describes a study of 1,000 popular apps using top analytic services in which we found misconfigurations in 120 apps. In 52 of the 120 apps, misconfigurations lead to a violation of either the analytic service providers' terms of service or the app's own privacy policy.
Year
DOI
Venue
2020
10.1145/3377811.3380401
International Conference on Software Engineering
Keywords
DocType
ISSN
Privacy, Mobile Application, Program Analysis, Analytic Services, Configuration
Conference
0270-5257
Citations 
PageRank 
References 
1
0.36
0
Authors
5
Name
Order
Citations
PageRank
Xueling Zhang121.39
Xiaoyin Wang218518.44
Rocky Slavin3344.83
Travis D. Breaux465547.75
Jianwei Niu527526.61