An Empirical Study on Developing Secure Mobile Health Apps: The
Developers Perspective
- URL: http://arxiv.org/abs/2008.03034v1
- Date: Fri, 7 Aug 2020 08:23:21 GMT
- Title: An Empirical Study on Developing Secure Mobile Health Apps: The
Developers Perspective
- Authors: Bakheet Aljedaani, Aakash Ahmad, Mansooreh Zahedi, M. Ali Babar
- Abstract summary: MHealth apps (mHealth apps for short) are becoming integral part of mobile and pervasive computing to improve the availability and quality of healthcare services.
Despite the offered benefits, mHealth apps face a critical challenge, i.e., security of health critical data that is produced and consumed by the app.
Several studies have revealed that security specific issues of mHealth apps have not been adequately addressed.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Mobile apps exploit embedded sensors and wireless connectivity of a device to
empower users with portable computations, context-aware communication, and
enhanced interaction. Specifically, mobile health apps (mHealth apps for short)
are becoming integral part of mobile and pervasive computing to improve the
availability and quality of healthcare services. Despite the offered benefits,
mHealth apps face a critical challenge, i.e., security of health critical data
that is produced and consumed by the app. Several studies have revealed that
security specific issues of mHealth apps have not been adequately addressed.
The objectives of this study are to empirically (a) investigate the challenges
that hinder development of secure mHealth apps, (b) identify practices to
develop secure apps, and (c) explore motivating factors that influence secure
development. We conducted this study by collecting responses of 97 developers
from 25 countries, across 06 continents, working in diverse teams and roles to
develop mHealth apps for Android, iOS, and Windows platform. Qualitative
analysis of the survey data is based on (i) 8 critical challenges, (ii)
taxonomy of best practices to ensure security, and (iii) 6 motivating factors
that impact secure mHealth apps. This research provides empirical evidence as
practitioners view and guidelines to develop emerging and next generation of
secure mHealth apps.
Related papers
- FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection [83.54960238236548]
FEDMEKI not only preserves data privacy but also enhances the capability of medical foundation models.
FEDMEKI allows medical foundation models to learn from a broader spectrum of medical knowledge without direct data exposure.
arXiv Detail & Related papers (2024-08-17T15:18:56Z) - A Developer-Centric Study Exploring Mobile Application Security Practices and Challenges [10.342268145364242]
This study explores the common practices and challenges that developers face in securing their apps.
Our findings show that developers place high importance on security, frequently implementing features such as authentication and secure storage.
We envision our findings leading to improved security practices, better-designed tools and resources, and more effective training programs.
arXiv Detail & Related papers (2024-08-16T22:03:06Z) - HIPAAChecker: The Comprehensive Solution for HIPAA Compliance in Android
mHealth Apps [0.0]
The proliferation of mobile health technology, or mHealth apps, has necessitated the paramount importance of safeguarding personal health records.
Many mobile app developers, including those of mHealth apps, are not fully cognizant of the HIPAA security and privacy guidelines.
This presents a unique opportunity for research to develop an analytical framework that can aid developers in maintaining a secure and HIPAA-compliant source code.
arXiv Detail & Related papers (2023-06-10T14:03:59Z) - A Comprehensive Picture of Factors Affecting User Willingness to Use
Mobile Health Applications [62.60524178293434]
The aim of this paper is to investigate the factors that influence user acceptance of mHealth apps.
Users' digital literacy has the strongest impact on their willingness to use them, followed by their online habit of sharing personal information.
Users' demographic background, such as their country of residence, age, ethnicity, and education, has a significant moderating effect.
arXiv Detail & Related papers (2023-05-10T08:11:21Z) - Multi-task Learning for Personal Health Mention Detection on Social
Media [70.23889100356091]
This research employs a multitask learning framework to leverage available annotated data to improve the performance on the main task.
We focus on incorporating emotional information into our target task by using emotion detection as an auxiliary task.
arXiv Detail & Related papers (2022-12-09T23:49:00Z) - An Empirical Study on Secure Usage of Mobile Health Apps: The Attack
Simulation Approach [0.0]
This study investigates the security awareness of mHealth app users via action-based research.
We simulated some common security attack scenarios in mHealth context and engaged a total of 105 app users to monitor their actions and analyse their behavior.
Our results indicate that whilst the minority of our participants perceived access permissions positively, the majority had negative views by indicating that such an app could violate or cost them to lose privacy.
arXiv Detail & Related papers (2022-11-14T18:10:34Z) - On the Privacy of Mental Health Apps: An Empirical Investigation and its
Implications for Apps Development [14.113922276394588]
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.
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.
arXiv Detail & Related papers (2022-01-22T09:23:56Z) - StudyMe: A New Mobile App for User-Centric N-of-1 Trials [68.8204255655161]
N-of-1 trials are multi-crossover self-experiments that allow individuals to systematically evaluate the effect of interventions on their personal health goals.
We present StudyMe, an open-source mobile application that is freely available from https://play.google.com/store/apps/details?id=health.studyu.me.
arXiv Detail & Related papers (2021-07-31T20:43:36Z) - Anxiety Detection Leveraging Mobile Passive Sensing [53.11661460916551]
Anxiety disorders are the most common class of psychiatric problems affecting both children and adults.
Leveraging passive and unobtrusive data collection from smartphones could be a viable alternative to classical methods.
eWellness is an experimental mobile application designed to track a full-suite of sensor and user-log data off an individual's device in a continuous and passive manner.
arXiv Detail & Related papers (2020-08-09T20:22:52Z) - Security and Privacy for mHealth and uHealth Systems: a Systematic
Mapping Study [0.0]
This study aims to identify, classify, compare, and evaluate state-of-the-art on security and privacy of m/uHealth systems.
arXiv Detail & Related papers (2020-06-22T08:44:49Z) - COVI White Paper [67.04578448931741]
Contact tracing is an essential tool to change the course of the Covid-19 pandemic.
We present an overview of the rationale, design, ethical considerations and privacy strategy of COVI,' a Covid-19 public peer-to-peer contact tracing and risk awareness mobile application developed in Canada.
arXiv Detail & Related papers (2020-05-18T07:40:49Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.