Hybrid blockchain for data sharing privacy -

Abstract

Due to the progress of smart mobile devices and web services, users have serious concerns about privacy in general, and location privacy in particular. These services allow service providers to collect huge amount of data from the users. In fact, the services that are provided leave the users unaware of where their data is stored or what logical computations are performed on it. Users have no control over their data anymore. In our work, we focus on preserving privacy, anonymity and transparency in a data-sharing environment. Companies are willing to pay big money to learn more about you and service providers are eager to gain as much information about you as possible. With all this information, experts can group data together and build a profile that exactly matches your character. Thus, trusting third parties may cause our privacy to be invaded (sold, analyzed, retargeted, and traded). As a response to these concerns, a number of centralized solutions have been proposed. However, none of these solutions solve the problem entirely. In particular, they tackle the problem from a specific point of view by limiting the service capabilities, which makes the solution inefficient. The challenges of data sharing are significant. Shifting from centralized services to decentralized services is a must to achieve trust and transparency. Blockchain, the technology behind distributed transactional applications, plays a fundamental role in decentralization. We believe that blockchain-based networks are the ultimate solution for solving the mentioned privacy problem. Hyperledger Fabric, a blockchain-based platform used to build decentralized applications, solves the problem of trusting third party. There is no need to have to trust the central hub; we have to trust the blockchain. Our goal is to build a hybrid end-to-end model that limits the privileges of the third party (service provider). However, we believe that service providers should also have access to some data while preserving transparency. Thus, our platform will us