Patient Controlled, Privacy Preserving IoT Healthcare Data Sharing Framework
Mohammad Jabed Morshed Chowdhury, A. S. M. Kayes, Paul Watters, Patrick Scolyer-Gray, Alex Ng · Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences · 2020
Healthcare data personally collected by individuals with wearable devices have become important sources of information for healthcare professionals and medical research worldwide. User-Generated Data (UGD) offers unique and sometimes fine-grained insight into the lived experiences and medical conditions of patients. The sensitive subject-matter of medical data can facilitate the exploitation and/or control of victims. Data collection in medical research therefore restricts access control over participant-data to the researchers. Therefore, cultivating trust with prospective participants concerned about the security of their medical data presents formidable challenges. Anonymization can allay such concerns, but at the cost of information loss. Moreover, such techniques cannot necessarily be applied on real-time streaming health data. In this paper, we aim to analyze the technical requirements to enable individuals to share their real-time wearable healthcare data with researchers without compromising privacy. An extension for delay-free anonymization techniques for real-time streaming health data is also proposed.