CRJul 29, 2021

Empirical Security and Privacy Analysis of Mobile Symptom Checking Applications on Google Play

arXiv:2107.13754v1
Originality Synthesis-oriented
AI Analysis

This highlights critical privacy risks for users of health apps, exposing sensitive data to exploitation, though it is an incremental analysis of existing apps.

The study analyzed 36 popular mobile symptom checking apps on Google Play and found they request excessive sensitive permissions and embed third-party tracking libraries, often sharing user data in unencrypted plain text, including to malicious domains.

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 targeted advertisements and analytics exploiting the privileged access of the SymptomCheckers in which they exist, as a mean of collecting and sharing critically sensitive data about the user and their device. We find that these are sharing the data that they collect through unencrypted plain text to the third-party advertisers and, in some cases, to malicious domains. The results reveal that the exploitation of SymptomCheckers is present in popular apps, still readily available on Google Play.

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