# Blockchain-Enabled Privacy-Preserving Ecosystem for DNA Sequence Sharing
## 2 Related Works  
The advent of advanced DNA sequencing technologies has facilitated the collection of extensive genomic data, raising significant concerns regarding the privacy and security of sensitive information. Addressing these challenges has been the focus of numerous studies, with blockchain technology emerging as a promising solution due to its decentralized and secure nature. [PERSON] [7] explored the potential application of blockchain and smart contracts to manage access rights to DNA sequence data, highlighting their suitability for automating access control rules in a decentralized manner. This approach underscores blockchain's potential to bridge the gap between researchers and the public regarding genomic data privacy concerns. Several studies have proposed blockchain-based frameworks for secure DNA data sharing. [PERSON] et al. [8] employed blockchain to secure data transmission among researchers, emphasizing the robustness of blockchain in ensuring data integrity during communication. [PERSON] et al. [9] introduced a three-layered general framework for DNA sequence storage, aimed at inspiring future research directions. Additionally, various studies [10; 11; 12] have implemented smart contract-based access control mechanisms to enhance the security and privacy of genomic data sharing. Despite these advancements, the large volume of DNA sequence data presents a significant challenge for on-chain storage. As an alternative, off-chain storage has been identified as a practical and efficient solution to address blockchain's data scalability challenges [13]. [PERSON] and [PERSON] [14] offer early insights into off-chaining computation and data, reinforcing the importance of moving bulky data off-chain to improve performance and scalability. This off-chain approach has been incorporated into many of these frameworks. A notable implementation of off-chain storage is presented by [PERSON] et al. [15], who integrated multiple heterogeneous offline databases into a private blockchain network. Their approach leveraged an integrator node to facilitate communication between the blockchain network and external databases, demonstrating the feasibility of hybrid solutions in managing large-scale genomic data. In recent years, blockchain integration in genomic data sharing has continued to evolve. For instance, [PERSON] et al. [16] developed ConsentChain, an Ethereum-based dynamic consent platform for clinical genomics that stores consent preferences on a permissioned blockchain while keeping genomic files off-chain. While ConsentChain improves the granularity of consent management, its reliance on Ethereum introduces performance and cost limitations (transaction throughput and fees) [17]. A 2022 perspective by [PERSON] et al. [18] proposed a private blockchain coupled with an NFT-based genomic data marketplace to incentivize data sharing, illustrating alternative approaches to encourage genomic data contributions. Furthermore, emerging studies emphasize self-sovereign identity and decentralized storage as key innovations for genomic data privacy--principles that our two-chain ecosystem adopts to empower users and protect sensitive information. In a related domain, [PERSON] et al. [6] extended the application of blockchain technology to physiological data sharing by adopting a decentralized digital identity framework initially proposed by [PERSON] [19]. This framework creates personal contracts for individual users, representing their digital identities in a decentralized manner. Users connect to their digital identities via digital wallets, eliminating reliance on traditional centralized identity providers such as Gmail or Facebook. While these studies have advanced the state of blockchain-based solutions for genomic and physiological data sharing, several limitations persist. The scalability of blockchain networks for large-scale genomic data remains a pressing challenge, as does the integration of heterogeneous datasets into cohesive systems.