Design and Implementation of a Privacy-Preserving Mobile Health Data Platform

Thesis Abstract

The increasing proliferation of mobile health (mHealth) applications has significantly enhanced access to healthcare services, yet it concurrently raises critical concerns regarding the privacy and security of sensitive health data. This study addresses the urgent need for a robust, scalable, and user-centric platform that ensures data privacy without compromising functionality or accessibility. The primary aim is to design, develop, and evaluate a privacy-preserving mobile health data platform that leverages advanced cryptographic techniques and privacy models to safeguard patient information while supporting seamless health data exchange among stakeholders such as patients, healthcare providers, and researchers. The specific objectives include analyzing existing privacy challenges in mHealth data management, designing an architecture incorporating privacy-enhancing technologies, implementing a prototype platform, and empirically evaluating its security, usability, and performance metrics. The research adopts a mixed-methods approach, combining qualitative and quantitative techniques. The study population comprises 150 active users of health monitoring apps, including 70 patients and 80 healthcare providers, sampled through stratified random sampling to ensure diversity in demographics and technological proficiency. Data collection instruments include structured questionnaires assessing user perceptions of privacy risks, interview guides for healthcare professionals on data sharing behaviors, and system logs capturing platform performance metrics. The platform implementation follows an iterative software development lifecycle, integrating cryptographic protocols such as attribute-based encryption (ABE) and secure multi-party computation (SMPC), alongside a comprehensive privacy model grounded in the Differential Privacy framework. System validation employs technical testing for vulnerability assessment, usability testing via the System Usability Scale (SUS), and performance analysis using response time and throughput metrics. Data analysis encompasses descriptive statistics, factor analysis for questionnaire validation, regression analysis to identify determinants of privacy concerns, and thematic analysis of interview data to elucidate stakeholder perspectives. It is anticipated that the results will demonstrate that the proposed platform effectively balances data privacy with functional utility, achieving high security standards validated through vulnerability testing, while maintaining acceptable usability scores (mean SUS score above 75). Performance evaluations are expected to show minimal latency overhead, confirming the platform's scalability for real-world deployment. The study also aims to reveal critical insights into user trust and behavioral factors influencing privacy adoption, informing best practices for mHealth data management. The research's primary contribution to knowledge lies in the novel integration of cryptographic techniques with user-centered privacy models in a mobile health context, providing a comprehensive framework for secure health data exchange. Additionally, the platform's architecture offers a scalable blueprint adaptable to various healthcare settings, contributing to advancements in health informatics standardization. The main conclusion underscores that privacy-preserving mechanisms embedded within user-friendly mobile health platforms are both feasible and essential for fostering trust and compliance with emerging data protection regulations. The study recommends that healthcare app developers prioritize integrated cryptographic solutions during system design phases and incorporate user education initiatives to enhance privacy awareness. Future research avenues include exploring blockchain-based solutions for decentralized data management, extending the platform to support emerging health data types such as genomics, and assessing long-term impacts on data sharing behaviors and patient outcomes. This study ultimately advocates for a paradigm shift in mHealth data stewardship, emphasizing the critical balance between technological innovation and ethical responsibility in safeguarding individual health information.