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dc.contributor.advisorCosta, Cristiano André da
dc.contributor.authorMayer, André Henrique
dc.date.accessioned2020-07-24T19:16:24Z
dc.date.accessioned2022-09-22T19:39:50Z
dc.date.available2020-07-24T19:16:24Z
dc.date.available2022-09-22T19:39:50Z
dc.date.issued2020-02-28
dc.identifier.urihttps://hdl.handle.net/20.500.12032/63538
dc.description.abstractThe Internet of Things adoption grows significantly and is successful in many different domains. Nevertheless, the ever-growing demand for more connected devices pushes the requirement for scalable IoT architectures capable of maintaining the security and privacy of collected data. The latter is a particularly critical aspect when considering sensitive data, e.g., medical records. One solution to address this challenge is to modify the centralized back-end model to one based on a Blockchain, changing the way IoT data is stored and shared by providing a decentralized peer-to-peer network. This technology enables naming and tracking for connected devices, and in the case of this article, it features a high availability of Personal Health Records, yet protecting patient’s privacy through the use of cryptography. Furthermore, the addition of fog computing mechanisms may assist healthcare applications to achieve faster local data processing, thus improving overall response time. As a result, devices have a local and more resilient ecosystem for operation. Our motivation lies when patients often leave their medical data scattered across various organizations (e.g. hospitals) as life events take them away from one provider’s data silo and into another, and, in doing so, they lose easy access to past data, as the provider, not the patient, generally retains primary stewardship. In this context, this work aims to propose an architecture model named FogChain, placing a distributed Blockchain network for management of patient’s personal health records, while integrating the Blockchain, Fog computing, and the Internet of Things technologies for the healthcare domain. Our expected main contribution is the FogChain model itself, and its concept of overcoming IoT constraints by adding an intermediary fog layer near to the edge to improve their capabilities and resources. To do so, a prototype was developed for evaluation, trough open-source projects, and structures for application development such as Node.js and Hyperledger Fabric Blockchain, while simulations and benchmarks were executed in a fog-like environment to collect metrics and information such as throughput and network latency regarding this technologies integrator. During our end-to-end experiments, the fog computing environment demonstrated a response time to be at least twice faster in comparison with cloud computing and pointed out that our proposed model is capable of achieving its goals of safely storing personal health records while retaining application performance. The FogChain implementation for PHR management demonstrated satisfactory proofs regarding the feasibility of FogChain architecture, while it demonstrated only a slice of how Blockchain could be employed in the healthcare domain, benefiting from its cryptographic and tamper-proof nature, which adds an additional security layer so necessary for healthcare applications, and in the meantime, it is safe to say that fog computing can play a big role in healthcare applications, providing local processing power, services, and increasing resources availability. However, more research, trials, and experiments must be carried out to ensure a secure and stable system is implanted before using our model in a real healthcare scenario, given the nature of patient’s health data being critical sensitive information.en
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superiorpt_BR
dc.languageenen
dc.publisherUniversidade do Vale do Rio dos Sinospt_BR
dc.rightsopenAccesspt_BR
dc.subjectInternet das coisaspt_BR
dc.subjectBlockchainen
dc.titleFogchain: a fog computing architecture integrating blockchain and Internet of things for personal health recordsen
dc.typeDissertaçãopt_BR


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