A Transparently-Secure and Robust Stock Data Supply Framework for Financial-Technology Applications

Recently, program trading has become the mainstream of financial information technology. The current FinTech applications mainly encounter three technical issues, including scalability, long-time retrieval, and security. Many small-and-medium companies seek economical solutions, while the three above properties are still met. In this paper, we propose Send-and-Subscribe (SaS) framework, aiming at providing a secure and robust financial stock data retrieval repository. In our survey to the related industries, the proposed novel framework is the first work on addressing the above three issues for financial computing areas. Finally, we conduct a set of experiments to validate the proposed framework on the real-world Taiwan stock data. The test results show the proposed framework indeed satisfies the security, scalability, and long-query requirements, comparing to existing solutions.