Hierarchical Data Integrity for IoT Devices in Connected Health Applications
Year: 2021
Type: article
Abstract: Internet of things devices are increasingly replacing expensive monitoring devices in many environments such as healthcare. People can eventually own their data, collected from smart personal devices, store them in a variety of cloud services, and make them available to service providers of their choice. In such cases, whenever service providers use these data to provide appropriate services, the data owner may become responsible for ensuring the integrity of data retrieved from multiple points. We present a Hierarchical Data Integrity (HDI) approach to verify if the data, sent by monitoring devices to the cloud, remain unchanged. It is hierarchical as follows: there is a quick verification of the integrity of recent health data (in less than 1 ms), followed if necessary by a low overhead secure option for verifying the integrity of both recent and historical data (still only in 6:1 ms). Further, the hierarchy allows granular identification of data units that fail integrity checks, without requiring any key sharing. It is possible for a data owner to periodically (randomly) use a more secure process to verify the integrity of data. This reduces the computation, storage, and time of integrity verification as shown by analysis, simulation, and hardware implementation.
Authors: Maryam Karimi, Prashant Krishnamurthy
Institution: University of Pittsburgh
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3211141428