Blockchain-based edge computing for medical data storage & processing using federated learning
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
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2021
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10361-149842022-01-26T10:18:23Z Blockchain-based edge computing for medical data storage & processing using federated learning Faiyaz, Fazle Rabbi Lisa, Afrin Sultana Rahat, Laisa Tabassum, Nafisa Istiaq, Walid Bin Mostakim, Moin Alam, Md. Golam Rabiul Department of Computer Science and Engineering, Brac University IoT Edge Computing Blockchain Federated Learning IPFS Edge computing This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 33-36). With a great number of IoT devices being used in healthcare and a massive rise in medical data produced by these devices, data storage and processing systems using the traditional cloud computing framework are not enough to meet real-time data re- requirements in Internet-based services as data is transferred to faraway cloud servers for processing, resulting in high latency and costs. Edge computing can provide a solution to this problem by effectively offloading a portion of the workload from the cloud to nearby edge servers to perform data processing tasks close to the end-users, thus reducing latency and cost as well as improving the quality of service. However, edge computing faces threats regarding data privacy and security due to edge nodes being more vulnerable to cyber-attacks. To address this problem, blockchain can be integrated to protect data from tampering, maintain data integrity, and allow reliable access, distributed computation, and decentralized data storage. Thus, in this research, we present a secure medical data storage and processing system using blockchain and edge computing to preserve our clients’ data privacy. To tackle privacy and security concerns, federated learning using a neural network has been used to train models locally using the data on the edge nodes rather than sending relevant private information to a centralized server for training, and model parameters, as well as IPFS file hashes and other private information, are securely stored on the blockchain by incorporating cryptographic techniques. Fazle Rabbi Faiyaz Nafisa Tabassum Laisa Rahat Walid Bin Istiaq Afrin Sultana Lisa B. Computer Science 2021-09-07T11:01:40Z 2021-09-07T11:01:40Z 2021 2021-06 Thesis ID 17101369 ID 16201055 ID 17201036 ID 17141023 ID 17101392 http://hdl.handle.net/10361/14984 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 36 pages application/pdf Brac University |
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Brac University |
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Institutional Repository |
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English |
topic |
IoT Edge Computing Blockchain Federated Learning IPFS Edge computing |
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IoT Edge Computing Blockchain Federated Learning IPFS Edge computing Faiyaz, Fazle Rabbi Lisa, Afrin Sultana Rahat, Laisa Tabassum, Nafisa Istiaq, Walid Bin Blockchain-based edge computing for medical data storage & processing using federated learning |
description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. |
author2 |
Mostakim, Moin |
author_facet |
Mostakim, Moin Faiyaz, Fazle Rabbi Lisa, Afrin Sultana Rahat, Laisa Tabassum, Nafisa Istiaq, Walid Bin |
format |
Thesis |
author |
Faiyaz, Fazle Rabbi Lisa, Afrin Sultana Rahat, Laisa Tabassum, Nafisa Istiaq, Walid Bin |
author_sort |
Faiyaz, Fazle Rabbi |
title |
Blockchain-based edge computing for medical data storage & processing using federated learning |
title_short |
Blockchain-based edge computing for medical data storage & processing using federated learning |
title_full |
Blockchain-based edge computing for medical data storage & processing using federated learning |
title_fullStr |
Blockchain-based edge computing for medical data storage & processing using federated learning |
title_full_unstemmed |
Blockchain-based edge computing for medical data storage & processing using federated learning |
title_sort |
blockchain-based edge computing for medical data storage & processing using federated learning |
publisher |
Brac University |
publishDate |
2021 |
url |
http://hdl.handle.net/10361/14984 |
work_keys_str_mv |
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