An advanced data fabric architecture leveraging homomorphic encryption and federated learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

Bibliografische gegevens
Hoofdauteurs:	Rieyan, Sakib Anwar, News, Md. Raisul Kabir, Rahman, A.B.M. Muntasir, Khan, Sadia Afrin, Zaarif, Sultan Tasneem Jawad
Andere auteurs:	Alam, Md. Golam Rabiul
Formaat:	Thesis
Taal:	English
Gepubliceerd in:	Brac University 2023
Onderwerpen:	Data fabric Federated learning Partially homomorphic encryption Big data Data integration (Computer science) Database management
Online toegang:	http://hdl.handle.net/10361/20203

id	10361-20203
record_format	dspace
spelling	10361-202032023-08-30T21:02:24Z An advanced data fabric architecture leveraging homomorphic encryption and federated learning Rieyan, Sakib Anwar News, Md. Raisul Kabir Rahman, A.B.M. Muntasir Khan, Sadia Afrin Zaarif, Sultan Tasneem Jawad Alam, Md. Golam Rabiul Department of Computer Science and Engineering, Brac University Data fabric Federated learning Partially homomorphic encryption Big data Data integration (Computer science) Database management This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 48-51). In this study, we present a novel approach for securely analyzing medical images using federated learning and partially homomorphic encryption within a distributed data fabric architecture. Our approach allows multiple parties to collaboratively train a machine learning model without exchanging raw data, while still maintaining compliance with laws and regulations such as HIPAA and GDPR. We demonstrate the effectiveness of our approach using pituitary tumor classification as a case study, achieving an overall accuracy of 83.31%. However, the primary focus of our work is on the development and evaluation of federated learning and partially homomorphic encryption as tools for secure medical image analysis. Our results show the potential for these techniques to be applied in other privacy-sensitive domains and contribute to the growing body of research on secure and privacy-preserving machine learning. Sakib Anwar Rieyan Md. Raisul Kabir News A.B.M. Muntasir Rahman Sadia Afrin Khan Sultan Tasneem Jawad Zaarif B. Computer Science 2023-08-30T04:47:48Z 2023-08-30T04:47:48Z 2023 2023-03 Thesis ID 19101024 ID 19101058 ID 19101042 ID 19101034 ID 19101206 http://hdl.handle.net/10361/20203 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. 51 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Data fabric Federated learning Partially homomorphic encryption Big data Data integration (Computer science) Database management
spellingShingle	Data fabric Federated learning Partially homomorphic encryption Big data Data integration (Computer science) Database management Rieyan, Sakib Anwar News, Md. Raisul Kabir Rahman, A.B.M. Muntasir Khan, Sadia Afrin Zaarif, Sultan Tasneem Jawad An advanced data fabric architecture leveraging homomorphic encryption and 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, 2023.
author2	Alam, Md. Golam Rabiul
author_facet	Alam, Md. Golam Rabiul Rieyan, Sakib Anwar News, Md. Raisul Kabir Rahman, A.B.M. Muntasir Khan, Sadia Afrin Zaarif, Sultan Tasneem Jawad
format	Thesis
author	Rieyan, Sakib Anwar News, Md. Raisul Kabir Rahman, A.B.M. Muntasir Khan, Sadia Afrin Zaarif, Sultan Tasneem Jawad
author_sort	Rieyan, Sakib Anwar
title	An advanced data fabric architecture leveraging homomorphic encryption and federated learning
title_short	An advanced data fabric architecture leveraging homomorphic encryption and federated learning
title_full	An advanced data fabric architecture leveraging homomorphic encryption and federated learning
title_fullStr	An advanced data fabric architecture leveraging homomorphic encryption and federated learning
title_full_unstemmed	An advanced data fabric architecture leveraging homomorphic encryption and federated learning
title_sort	advanced data fabric architecture leveraging homomorphic encryption and federated learning
publisher	Brac University
publishDate	2023
url	http://hdl.handle.net/10361/20203
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An advanced data fabric architecture leveraging homomorphic encryption and federated learning

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