论文标题

关于心理健康应用的隐私:实证研究及其对应用程序开发的影响

On the Privacy of Mental Health Apps: An Empirical Investigation and its Implications for Apps Development

论文作者

Iwaya, Leonardo Horn, Babar, M. Ali, Rashid, Awais, Wijayarathna, Chamila

论文摘要

通过移动系统提供了越来越多的心理健康服务,这是一种称为MHealth的范式。尽管通过MHealth系统的采用率有前所未有的增长,部分是由于19日大流行,但由于安全漏洞而引起的数据隐私风险的担忧也在增加。尽管一些研究已经从不同角度(包括安全)分析了MHealth应用程序,但在用于精神卫生服务的MHealth应用程序中可能存在的数据隐私问题的证据相对较少,其接受者可能会特别脆弱。本文报告了一项实证研究,旨在系统地识别和理解精神健康应用中纳入的数据隐私。我们分析了Google Play商店的27个顶级心理健康应用程序。我们的方法使我们能够对应用程序进行深入的隐私分析,涵盖静态和动态分析,数据共享行为,服务器端测试,隐私影响评估请求和隐私政策评估。此外,我们将发现结果映射到了Linddun威胁分类法,描述了威胁如何在研究应用程序上表现出来。这些发现揭示了重要的数据隐私问题,例如不必要的权限,不安全的加密实现以及日志和Web请求中个人数据和凭据的泄漏。由于应用程序的开发没有提供可连接性,可检测性和可识别性的万无一失的机制,因此也存在用户分析的高风险。当前应用程序的生态系统中的第三方和广告商之间的数据共享使这种情况加剧了。根据这项研究的经验发现,我们提供建议,尤其是MHealth应用程序的不同利益相关者,尤其是应用程序开发人员。 [...]

An increasing number of mental health services are offered through mobile systems, a paradigm called mHealth. Although there is an unprecedented growth in the adoption of mHealth systems, 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 third 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. [...]

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源