Amanuensis: Information Provenance for Health-Data Systems
Journal of Information Systems Management and Security
Department of Computer Science
Mobile health (mHealth) apps and devices are increasingly popular for health research, clinical treatment, and personal wellness, as they offer the ability to continuously monitor aspects of individuals’ health as they go about their everyday activities. Combining the data produced by these mHealth devices may give healthcare providers a more holistic view of a patient’s health, increase the level of patient care, and reduce operating costs. Creating a trusted and secure data sharing ecosystem for mHealth devices is difficult, however, as devices are implemented with different technologies and managed by different organizations. To address these issues, we present Amanuensis: a concept for a secure, integrated healthcare data system that leverages Blockchain and Trusted Execution Environment (TEE) technologies to achieve information provenance for mHealth data. By using a blockchain to record and enforce data-access policies, we remove the need to trust a single entity with gate-keeping the health data. Instead, participating organizations form a consortium to share responsibility for verifying data integrity and enforcing access policies for data stored in private data silos. Data accesses and computations take place inside of TEEs to preserve data confidentiality and to provide a verifiable attestation report that can be stored on the blockchain for the purpose of information provenance. We evaluate a prototype implementation of Amanuensis – built using Intel SGX trusted execution hardware and the VeChain Thor blockchain platform – which shows that Amanuensis is capable of supporting up to 14,256,000 mHealth data sources at $0.07 per data source per day.
Taylor Hardin and David Kotz. Amanuensis: Information Provenance for Health-Data Systems. Journal of Information Systems Management and Security, volume 58, number 2, article 102460, 21 pages. Elsevier, March 2021. doi:10.1016/j.ipm.2020.102460.
Dartmouth Digital Commons Citation
Hardin, Taylor and Kotz, David, "Amanuensis: Information Provenance for Health-Data Systems" (2021). Dartmouth Scholarship. 4051.