Enhanced Security and Privacy for Blockchain-enabled Electronic Medical Records in eHealth.

PhD Theses.Electronic medical records (EMRs) as part of an eHealth system are vital assets centrally managed by medical institutions and used to maintain up to date patients' medical histories. Such centralised management of EMRs may result in an increased risk of EMR damage or loss to medical institutions. In addition, it is di cult to monitor and control who can access their EMRs and for what reasons as eHealth may increasingly involve the use of IoT devices such as eHealth wearables and distributed networks. Blockchain is proposed as a promising method applied to support distributed data storage to maintain and share EMRs using its inherent immutability (forgery resistance). However, the original blockchain design cannot restrict unauthenticated or unauthorised data access for use as part of EMR management. Therefore, two novel authorisation schemes to enhance the security and privacy of blockchain use for EMRs are proposed in this work. The rst one can omit the agent layer (gateway) to authorise users' access to blockchain-enabled EMRs with block level gran- ularity, whilst maintaining compatibility with the underlying Blockchain data structure. Then, an improved scheme is proposed to implement multiple levels of granularity autho- risation, whilst supporting exible data queries. This scheme dispenses with the need to use a public key infrastructure (PKI) in authorisation and hence reduces the resource cost of computation and communication. Furthermore, to realise privacy preservation during authorisation, a challenge-response anonymous authorisation is proposed that avoids the disclosure of users' credentials when authorising data access requests. Compared with the baseline schemes, the proposed authorisation schemes can decrease the time consumption of computation and data transmission and reduce the transmitted data size so that they can be used in low-resource IoT devices applied to blockchain- enabled EMRs as demonstrated in performance experiments. In addition, theoretical i validations of correctness demonstrate that the proposed authorisation schemes work correctly

Blockchain leveraged decentralized IoT eHealth framework

Blockchain technologies recently emerging for eHealth, can facilitate a secure, decentral- ized and patient-driven, record management system. However, Blockchain technologies cannot accommodate the storage of data generated from IoT devices in remote patient management (RPM) settings as this application requires a fast consensus mechanism, care- ful management of keys and enhanced protocols for privacy. In this paper, we propose a Blockchain leveraged decentralized eHealth architecture which comprises three layers: (1) The Sensing layer –Body Area Sensor Networks include medical sensors typically on or in a patient body transmitting data to a smartphone. (2) The NEAR processing layer –Edge Networks consist of devices at one hop from data sensing IoT devices. (3) The FAR pro- cessing layer –Core Networks comprise Cloud or other high computing servers). A Patient Agent (PA) software replicated on the three layers processes medical data to ensure reli- able, secure and private communication. The PA executes a lightweight Blockchain consen- sus mechanism and utilizes a Blockchain leveraged task-offloading algorithm to ensure pa- tient’s privacy while outsourcing tasks. Performance analysis of the decentralized eHealth architecture has been conducted to demonstrate the feasibility of the system in the pro- cessing and storage of RPM data

A patient agent controlled customized blockchain based framework for internet of things

Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph