Empirical Security and Privacy Analysis of Mobile Symptom Checking Applications on Google Play
I Wayan Budi Sentana, Muhammad Ikram, Mohamed Ali Kaafar, Shlomo, Berkovsky

TL;DR
This study conducts a comprehensive analysis of 36 popular mobile SymptomChecker apps on Google Play, revealing significant privacy and security issues including excessive permissions, third-party tracking, and unencrypted data sharing, which pose risks to user privacy.
Contribution
It introduces a combined static and dynamic analysis approach to detect and categorize security and privacy vulnerabilities in SymptomChecker apps, highlighting prevalent risks in popular health apps.
Findings
High number of sensitive permissions requested
Widespread use of third-party tracking libraries
Sharing of sensitive data via unencrypted channels
Abstract
Smartphone technology has drastically improved over the past decade. These improvements have seen the creation of specialized health applications, which offer consumers a range of health-related activities such as tracking and checking symptoms of health conditions or diseases through their smartphones. We term these applications as Symptom Checking apps or simply SymptomCheckers. Due to the sensitive nature of the private data they collect, store and manage, leakage of user information could result in significant consequences. In this paper, we use a combination of techniques from both static and dynamic analysis to detect, trace and categorize security and privacy issues in 36 popular SymptomCheckers on Google Play. Our analyses reveal that SymptomCheckers request a significantly higher number of sensitive permissions and embed a higher number of third-party tracking libraries for…
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