Designing security of personal data in distributed health care platform
Journal Title: Технологический аудит и резервы производства - Year 2018, Vol 4, Issue 2
Abstract
<p><em>The object of research is the design of EHR system capable for both patient-physician communication and secure and privacy preserving cross-organisational analytical collaboration. Constant patient monitoring and amount of quality data available for further analysis is crucial for more accurate medical recommendations and therefore general wellbeing. On the other hand, most of the current architectural approaches are subject to different vulnerabilities to data integrity and can’t provide multi-party computations (MPC) proof from sensitive information leakage resulting in very fragmented datasets available for each clinic or health organisation. Another improvement area is edge level sensor network communication security.</em></p><p><em>In this paper it is proposed to split architecture into layers with dedicated security zones. This fragmentation allows to effectively segment infrastructure, allowing each element to apply to its own authentication and authorization requirements as well as secure data individually. Side effect of this approach is reducing network load and eliminating security and privacy issues by minimising sensitive data transfer (e. g. basic data gathering and processing is being performed on the smart sensors). Usage of Hyperledger is suggested for maintaining data integrity with off-chain database for optimizing transactions storage and speed. Utilization of MPC allows to share records between akin organisations for joint calculations and ml-models training without revealing actual data.</em></p><p><em>Suggested approaches allow building robust and flexible yet secure platform for sensitive data gathering, analysis and multi-party processing without revealing users’ identities leveraging advantages of edge computing, Hyperledger and joint data calculations.</em></p>
Authors and Affiliations
Anatolii Petrenko, Roman Kyslyi, Ihor Pysmennyi
Keywords
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- EP ID EP527458
- DOI 10.15587/2312-8372.2018.141299
- Views 164
- Downloads 0
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