Privacy Preserving Co-operative Statistical Analysis for Computing Medical Data
K. Harini · 2014
Mobile Healthcare (m-Healthcare) system has been envisioned as an important application of pervasive computing to improve health care quality and save lives of people, where small wearable or implantable body sensor nodes and smart phones are utilized to provide remote healthcare monitoring to people who have chronic medical conditions such as diabetes and heart disease , in a mobile healthcare system, medical users are no longer needed to be monitored within home or hospital environments. Instead, after being equipped with smart phone and wireless body sensor network (BSN) formed by body sensor nodes, the medical users can walk outside and receive the high-quality healthcare monitoring from medical professionals anytime and anywhere. Each mobile medical user’s personal health information (PHI) such as heart beat, blood sugar level, blood pressure and temperature , can be first collected by the BSN, and then generated by smart phone via Bluetooth. Finally, they are transmitted to the remote healthcare center using the nearby access point via wi-fi network. When the PHI is being transmitted there are many possibilities that a third person may hack the information. To avoid this scenario we introduce a new Privacy Preserving Scalar Product Computation (PPSPC) technique in the client side also.