zkIgnite 3: Mina Domain Name Service

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zkIgnite 3: Mina Domain Name Service

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MiDNA addresses the need for analyzing the presence or absence of rare or genetic diseases through its specialized service. This solution offers benefits for both individuals providing genomic data and the companies tasked with analyzing it. For individuals, MiDNA provides the ZKApp (MiDNA Client), operating offline, which enables them to analyze their genomic data without compromising its confidentiality. Users can access the analyzed results securely by authenticating their identity and providing a designated amount of gas using Mina. Importantly, only personal and genomic data is transmitted, ensuring privacy and security for the individual’s sensitive health information. For analysis service providers, MiDNA facilitates targeting customers who prioritize privacy when utilizing analysis services. By integrating payments through Mina, providers can establish a stable payment channel while contributing to the growth of the Mina ecosystem through application utilization. To capitalize on these benefits, the team leveraged the o1.js library based on ZKP-snark and Protokit to develop off-chain/on-chain services that operate seamlessly with Mina. Challenges encountered Several challenges arose during the project development: Transitioning from Solidity to Protokit presented a learning curve, impacting user experience and comprehension, especially within the constraints of a hackathon timeframe. Greater diversity in use cases could enhance ease of development. The scope of applying Zero-Knowledge Proofs (ZKP) was initially limited to anonymity, necessitating efforts to broaden its applicability while preserving anonymity. The proof-of-concept for genome sequencing revealed the need for extensive modifications to realize actual services, particularly due to the vast size of genomic data. During the hackathon, simplification strategies were employed, focusing on extracting basic sequences, converting specific sequence similarities into scores, and visualizing the data. Team Members Taelim Hwang / Dohyun Kim Github Link > Info Page > https://youtu.be/3X3d16InmYg?feature=shared