Biyoinformatik Alanı için Blokzincir Tabanlı Veri Paylaşım Platformu
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2020, 2020
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Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü
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Abstract
Son zamanlarda, panomik çalışmalar -omik verileri ile diğer veri türlerini birleştirerek, yeni ve uygulanabilir biyobelirteçleri belirlemeye çalışmaktadır. Bu bağlamda omik verilerinin doğru analizi için veri paylaşımının yanı sıra veri gizliliği ve sahipliği sorunlarını çözen, etik yönleri dikkate alan güvenli platformların geliştirilmesine ihtiyaç vardır. Bugünlerde blokzincir teknolojisi, farklı bir perspektiften bu sorunlara yönelik yeni bir çözüm sunduğu için genomik alanında büyük ilgi görmektedir. Bu tezde, verimli genomik veri paylaşımını sağlamak, genomik veriler üzerinde istatistiksel analiz ve benzeri işlemleri yapmak için blokzinciri, homomorfik şifreleme ve intel yazılım koruması uzantısına (SGX) dayanan, GenShare adlı hibrit bir platform önermekteyiz. Önerilen model, homomorfik şifreleme ve SGX kullanarak güvenlik gizliliği sorunlarını çözerken, diğer sorunları Hyperledger Fabric ve Ethereum ağlarının bir kombinasyonunu kullanarak çözmektedir. Bu çalışmada, GenShare modelinin ilk aşaması olan Hyperledger Fabric ağ kurulumu yapılmış ve farklı sayıda iş yükü ile ağın performansı test edilmiştir. Performans değerlendirmelerimizin sonucunda, GenShare modelinin veri toplama ve paylaşma sürecini hızlandıracağı, ve kullanıcalar için verimli bir platform olacağı sonucuna varılmıştır.
Recently, panomics studies attempt to identify new and actionable biomarkers by combining -omics data with other data types. In this context, there is a need to develop secure platforms that take into account ethical aspects and solve privacy and ownership issues as well as data sharing for an accurate analysis of -omics data. These days, blockchain technology has picked up significant attention in genomics, since it offers a new solution to these problems from a different perspective. In this thesis, we proposed a hybrid platform called GenShare, which is based on blockchain, homomorphic encryption and intel software guard extension (SGX) to provide efficient genomic data sharing, to perform statistical analysis and other similar processes on genomic data. While the proposed model solves security-privacy issues using homomorphic encryption and SGX, it solves other issues by using a combination of Hyperledger Fabric and Ethereum networks. In this study, Hyperledger Fabric network, which is the first phase of the GenShare model, setup is made and the performance of the network is tested with a different number of workloads. At the end of our performance evaluations, we concluded that the GenShare model has a potential to speed up the process of collecting and sharing data and it offers an efficient platform for the participants.
Recently, panomics studies attempt to identify new and actionable biomarkers by combining -omics data with other data types. In this context, there is a need to develop secure platforms that take into account ethical aspects and solve privacy and ownership issues as well as data sharing for an accurate analysis of -omics data. These days, blockchain technology has picked up significant attention in genomics, since it offers a new solution to these problems from a different perspective. In this thesis, we proposed a hybrid platform called GenShare, which is based on blockchain, homomorphic encryption and intel software guard extension (SGX) to provide efficient genomic data sharing, to perform statistical analysis and other similar processes on genomic data. While the proposed model solves security-privacy issues using homomorphic encryption and SGX, it solves other issues by using a combination of Hyperledger Fabric and Ethereum networks. In this study, Hyperledger Fabric network, which is the first phase of the GenShare model, setup is made and the performance of the network is tested with a different number of workloads. At the end of our performance evaluations, we concluded that the GenShare model has a potential to speed up the process of collecting and sharing data and it offers an efficient platform for the participants.
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Computer Engineering And Computer Science And Control, Bilgisayar Mühendisliği Bilimleri-Bilgisayar Ve Kontrol
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