Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab
Alya Masitha
Institut Teknologi Statistika dan Bisnis Muhammadiyah (ITESA Muhammadiyah) Semarang
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
MODEL PERANCANGAN SISTEM TERDESENTRALISASI UNTUK KEAMANAN DATA GENETIKA MANUSIA BERBASIS BLOCKCHAIN DAN IPFS Tri Stiyo Famuji; Alya Masitha; Maulana Muhammad Jogo Samodro; Galih Pramuja Inngam Fanani; Yuniariana Pertiwi
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6015

Abstract

The rapid development of genomic technology has heightened the urgency to address vulnerabilities in centralized systems managing sensitive human genetic data. This study proposes a decentralized system integrating blockchain and IPFS to enhance data security, integrity, and accessibility. Blockchain ensures immutable audit trails and dynamic access control via smart contracts, while IPFS provides scalable off-chain storage using cryptographic hashes (CIDs). The hybrid design separates raw data storage (encrypted via homomorphic encryption) on IPFS from access management on the Ethereum blockchain. A user interface built with React.js and Web3.js enables encrypted data uploads, role-based access requests, and real-time audit monitoring, complying with GDPR/HIPAA standards. Testing demonstrated the system’s effectiveness in preventing unauthorized access and ensuring data traceability. Challenges such as energy efficiency and regulatory compliance were addressed through sharding, layer-2 protocols, and selective data deletion mechanisms. This framework supports secure cross-institutional collaboration in genomic research, promoting public participation and accelerating biomedical innovation. Future work will focus on optimizing computational efficiency and expanding datasets.
Co-Authors Galih Pramuja Inngam Fanani Maulana Muhammad Jogo Samodro Tri Stiyo Famuji Yuniariana Pertiwi