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

Lin Yi Jiang, Cheng Ju Kuo, Yu Hsin Wang, Mu En Wu, Wei Tsung Su, Ding Chau Wang, O. Tang-Hsuan, Chi Luen Fu, Chao Chun Chen

研究成果: Conference contribution

摘要

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.

原文English
主出版物標題Intelligent Information and Database Systems - 13th Asian Conference, ACIIDS 2021, Proceedings
編輯Ngoc Thanh Nguyen, Suphamit Chittayasothorn, Dusit Niyato, Bogdan Trawiński
發行者Springer Science and Business Media Deutschland GmbH
頁面616-629
頁數14
ISBN(列印)9783030732790
DOIs
出版狀態Published - 2021
事件13th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2021 - Phuket, Thailand
持續時間: 2021 四月 72021 四月 10

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12672 LNAI
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference13th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2021
國家/地區Thailand
城市Phuket
期間21-04-0721-04-10

All Science Journal Classification (ASJC) codes

  • 理論電腦科學
  • 電腦科學(全部)

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