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Algebraic secret sharing using privacy homomorphisms for IoT-based healthcare systems

1 Department of Computer Science, University of Warwick, Coventry, United Kingdom
2 School of Information Technology, Deakin University, Geelong, Australia

Special Issues: Security and Privacy Protection for Multimedia Information Processing and communication

Healthcare industry is one of the promising fields adopting the Internet of Things (IoT) solutions. In this paper, we study secret sharing mechanisms towards resolving privacy and security issues in IoT-based healthcare applications. In particular, we show how multiple sources are possible to share their data amongst a group of participants without revealing their own data to one another as well as the dealer. Only an authorised subset of participants is able to reconstruct the data. A collusion of fewer participants has no better chance of guessing the private data than a non-participant who has no shares at all. To realise this system, we introduce a novel research upon secret sharing in the encrypted domain. In modern healthcare industry, a patient’s health record often contains data acquired from various sensor nodes. In order to protect information privacy, the data from sensor nodes is encrypted at once and shared among a number of cloud servers of medical institutions via a gateway device. The complete health record will be retrieved for diagnosis only if the number of presented shares meets the access policy. The retrieval procedure does not involve decryption and therefore the scheme is favourable in some time-sensitive circumstances such as a surgical emergency. We analyse the pros and cons of several possible solutions and develop practical secret sharing schemes for IoT- based healthcare systems.
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Keywords healthcare systems; homomorphic encryption; Internet of things; secret sharing

Citation: Ching-Chun Chang, Chang-Tsun Li. Algebraic secret sharing using privacy homomorphisms for IoT-based healthcare systems. Mathematical Biosciences and Engineering, 2019, 16(5): 3367-3381. doi: 10.3934/mbe.2019168


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