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

AAQ-PEKS: An Attribute-based Anti-Quantum Public-Key Encryption Scheme with Keyword Search for E-healthcare Scenarios

Electronic Medical Records (EMRs) have been utilized in plentiful medical institutions due to their superior convenience and low storage overhead. Nevertheless, it is difficult for medical departments with disparate management regulations to share EMRs through secure communication channels since sensitive EMRs are prone to be tampered with. Therefore, the EMRs should be encrypted before being outsourced to the network servers. Public key Encryption with Keyword Search (PEKS) has the ability for doctors to search encrypted EMRs, but traditional PEKS algorithms are susceptible to quantum computing attacks and without considering access control. To address the aforementioned issues, we proposed AAQ-PEKS scheme, named an attribute-based anti-quantum public-key encryption scheme with keyword search. Initially, based on the LWE hardness, we first introduce the attribute-based PEKS that can resist quantum attacks in E-health scenarios. Secondly, we combine Attribute-Based Encryption (ABE) into AAQ-PEKS to realize access control for sensitive EMRs. Thirdly, the computational security analysis illustrates that our scheme achieves correctness, Indistinguishability against Chosen Plaintext Attack (IND-CPA) and Indistinguishability against Chosen Keyword Attack (IND-CKA). Lastly, comprehensive performance evaluation in practice elaborates that our AAQ-PEKS is more efficient compared with other existing top-tier schemes. To conclude, our scheme has the characteristics of resisting quantum attacks and fine-grained access control for E-health scenarios

Responsible AI and Analytics for an Ethical and Inclusive Digitized Society

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