CSR: Small: Collaborative Research: CAM: A Cloud-Assisted mHealth Monitoring System

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Mobile Health (mHealth), particularly mobile healthcare monitoring, has been perceived to be the most dynamic mobile apps which play a crucial role in revolutionizing healthcare industries and steadily improving the quality of individuals' lives. Unfortunately, due to the sensitive and private nature of the health and fitness related data handled by mHealth monitoring services, privacy issues become the stumbling blocks to wide deployment and must be addressed. With limited capital investments, small to medium sized mHealth companies may have to seek cloud computing facilities to reduce the cost on IT support. However, outsourcing to the cloud will aggravate the privacy issues since companies' monitoring programs are also proprietary information. This project focuses on designing an architectural framework, called CAM: a cloud-assisted mHealth monitoring system, developing it into a middleware, and outsourcing expensive computations to the cloud. At a high level, the proposed research is to develop an enabling technology for the potentially wide adoption of mHealth monitoring services. In particular, a security framework is designed to preserve the privacy of users' health and fitness data and companies' monitoring programs while still allowing the cloud to correctly execute the programs and return proper advices to users. The design takes the outsourcing paradigm into account by shifting most computationally intensive tasks to the cloud while still preserving privacy, which is the key to producing a practically deployable system. The framework is then developed into a middleware by tackling practical issues such as a suitable programming model, balancing between security guarantees and flexibility for app developers, etc. Comprehensive penetration testing is conducted by simulating unique attacks to evaluate the security of the proposed framework in practical system settings. Although motivated by mHealth monitoring applications, the proposed security framework can be generalized for privacy-preserving outsourcing of diagnostic programs which have many other important applications such as financial analysis and software fault diagnosis. The proposed research will thus have broader impact by contributing to multiple disciplines and offering both graduate and undergraduate students plentiful opportunities for multidisciplinary research.