Secure Digital Health Data Management in Internet of Things Using Blockchain and Machine Learning

Abstract

Advancements in technology have led to dramatic development in the healthcare industry leading to rising demand for better data security and privacy. The medical field is revolutionized by emerging technologies like Artificial Intelligence (AI) and Internet of Things (IoT) for digital health tracking and remote diagnosis. Recently, medical data management systems are encountering challenges in terms of transparency, provenance and traceability of data since most systems use centralized databases which require third-party involvement. The smart technology AI and the immutable technology blockchain can potentially reshape the secure handling of this data. In this chapter, a two-part novel model is proposed to allay any security and privacy concerns in Internet of Healthcare Things. The first part analyses a patient's health parameters using machine learning, detects and discards anomalous data and stores the non-anomalous data with findings in a transparent, secure fashion using blockchain. The second part provides a secure way to preserve critical medical records in blockchain using sandboxed Secure Virtual Machines to avoid any of the privacy issues and computational power constraints of currently existing solutions making this model very secure. Using our model, crucial healthcare data is managed in a secure and transparent fashion within the bounds of the IoHT ecosystem, while also preserving the confidentiality of the concerned parties.