Iwaya Leonardo Horn, Babar M Ali, Rashid Awais, Wijayarathna Chamila
Centre for Research on Engineering Software Technologies, The University of Adelaide, Adelaide, SA 5005 Australia.
Cyber Security Cooperative Research Centre (CSCRC), Joondalup, Australia.
Empir Softw Eng. 2023;28(1):2. doi: 10.1007/s10664-022-10236-0. Epub 2022 Nov 8.
An increasing number of mental health services are now offered through mobile health (mHealth) systems, such as in mobile applications (apps). Although there is an unprecedented growth in the adoption of mental health services, partly due to the COVID-19 pandemic, concerns about data privacy risks due to security breaches are also increasing. Whilst some studies have analyzed mHealth apps from different angles, including security, there is relatively little evidence for data privacy issues that may exist in mHealth apps used for mental health services, whose recipients can be particularly vulnerable. This paper reports an empirical study aimed at systematically identifying and understanding data privacy incorporated in mental health apps. We analyzed 27 top-ranked mental health apps from Google Play Store. Our methodology enabled us to perform an in-depth privacy analysis of the apps, covering static and dynamic analysis, data sharing behaviour, server-side tests, privacy impact assessment requests, and privacy policy evaluation. Furthermore, we mapped the findings to the LINDDUN threat taxonomy, describing how threats manifest on the studied apps. The findings reveal important data privacy issues such as unnecessary permissions, insecure cryptography implementations, and leaks of personal data and credentials in logs and web requests. There is also a high risk of user profiling as the apps' development do not provide foolproof mechanisms against linkability, detectability and identifiability. Data sharing among 3rd-parties and advertisers in the current apps' ecosystem aggravates this situation. Based on the empirical findings of this study, we provide recommendations to be considered by different stakeholders of mHealth apps in general and apps developers in particular. We conclude that while developers ought to be more knowledgeable in considering and addressing privacy issues, users and health professionals can also play a role by demanding privacy-friendly apps.
The online version contains supplementary material available at 10.1007/s10664-022-10236-0.
现在越来越多的心理健康服务通过移动健康(mHealth)系统提供,比如移动应用程序(app)。尽管心理健康服务的采用率有前所未有的增长,部分原因是新冠疫情,但因安全漏洞导致的数据隐私风险担忧也在增加。虽然一些研究从不同角度分析了移动健康应用程序,包括安全性,但对于用于心理健康服务的移动健康应用程序中可能存在的数据隐私问题,证据相对较少,而这些应用程序的用户可能特别脆弱。本文报告了一项实证研究,旨在系统地识别和理解心理健康应用程序中包含的数据隐私。我们分析了谷歌应用商店中排名前27的心理健康应用程序。我们的方法使我们能够对这些应用程序进行深入的隐私分析,包括静态和动态分析、数据共享行为、服务器端测试、隐私影响评估请求以及隐私政策评估。此外,我们将研究结果映射到LINDDUN威胁分类法,描述威胁在研究的应用程序上是如何表现的。研究结果揭示了重要的数据隐私问题,如不必要的权限、不安全的加密实现,以及日志和网络请求中个人数据和凭证的泄露。由于应用程序的开发没有提供防止可链接性、可检测性和可识别性的万无一失的机制,因此用户画像的风险也很高。当前应用程序生态系统中第三方和广告商之间的数据共享加剧了这种情况。基于本研究的实证结果,我们提出了一些建议,供移动健康应用程序的不同利益相关者,特别是应用程序开发者考虑。我们得出结论,虽然开发者在考虑和解决隐私问题时应该更有见识,但用户和健康专业人员也可以通过要求使用隐私友好型应用程序发挥作用。
在线版本包含可在10.1007/s10664-022-10236-0获取的补充材料。