Abstract:
With the rapid advancement of technology, context-aware services, ubiquitous technology, and pervasiveness, systems have revolutionized the healthcare sector, offering substantial benefits. Context-aware e-health services have emerged as a promising solution to enhance patient healthcare by continuously monitoring their health status and providing timely assistance during medical emergencies. However, the seamless monitoring of patients' context and health information gives rise to concerns regarding privacy and trust, particularly in terms of ensuring the reliability, integrity, and authenticity of authorized users accessing sensitive patient information. The primary objective of this thesis is to address these concerns and establish a secure trust model for handling patients' contextual and health information, while simultaneously fostering trust among patients, medical personnel, and administrators. The proposed trust model serves as a robust approach to evaluating trust in the context of e-health services. By considering key trust factors such as privacy, reliability, credibility, and transparency the model enables users to make informed decisions when choosing medical personnel. It also employs a well-defined computation formula to cultivate trust within the context-aware e-health ecosystem. The computation results of the proposed model outperform other Trust-Based Personalized Service models, the model obtained a precision of 1.0. Furthermore, the integration of blockchain technology further enhances the security and integrity of the system, ensuring that sensitive patient information remains tamper-proof and protected from unauthorized access. This trust model significantly contributes to the advancement of trust models in the context-aware e-health domain, facilitating improved user experiences and promoting the wider adoption of context-aware e-health services.
