USING JIFF FOR COLLABORATIVE MEDICAL DATA ANALYSIS WITH SECURE MULTIPARTY COMPUTATION

In collaborative data analysis, secure multiparty computation can be utilised to compute statistical functions in a private manner. For the purpose of developing apps that require safe multi-party collaboration, JIFF is an open-source JavaScript library. We use JIFF to create an application that all...

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Bibliographic Details
Published in:Proceedings on Engineering Sciences
Main Authors: Usha Divakarla, K Chandrasekaran, K Hemanth Kumar Reddy
Format: Article
Language:English
Published: University of Kragujevac 2025-03-01
Subjects:
secure multiparty computation
collaborative data analysis
jiff
data privacy
secret sharing scheme
Online Access:https://pesjournal.net/journal/v7-n1/68.pdf
Description
Summary:In collaborative data analysis, secure multiparty computation can be utilised to compute statistical functions in a private manner. For the purpose of developing apps that require safe multi-party collaboration, JIFF is an open-source JavaScript library. We use JIFF to create an application that allows two parties to collaborate on medical data analysis, including the processing of sensitive patient data while maintaining data confidentiality and privacy. A decentralized system that ensures data security and secure computation of private information is provided by the JIFF framework. We assess the system's functionality and privacy-preserving skills, proving that it can effectively protect data privacy while still producing reliable analysis findings.
ISSN:2620-2832
2683-4111

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