Secure and Privacy-Preserving Referral Framework for E-Health System

Doctors have a crucial role in promoting the physical wellbeing of patients and ensuring that they are given the safest and effective treatments that meet their medical needs and preferences. Due to an extensive area of the field of medicine, doctors do not have complete knowledge about a patient diagnosis and the special tools required, hence there is need for referral. Referral requires the transfer of patients and their sensitive medical information to a specialist in order to develop a tailored treatment or suggestion for a better healthcare treatment. Therefore, it is imperative to search for a specialist in that area of specialization who will not only have access to the patient’s relevant health information but also be able to proffer solutions to health challenges. However, if this is not done securely and anonymously, it would not only affect the confidentiality of the data but also exposes the privacy of patient and physicians to adversaries. Therefore, there is need for an efficient referral framework that is capable of securing patient's data, and protecting patient's and physician's identities during the referral. In this paper, we proposed a referral framework with efficient security and privacy schemes for achieving anonymous authentication during the referral process and a trust model for efficient rating and selection of specialists. To preserve privacy of the physicians, we leverage pseudonyms for anonymous authentication. A time-bound group signature was proposed by modifying existing group signatures for a robust grouping of physicians based on their specialisations and a trust model for determining the competency of specialist.