Ant Group, China's fintech giant, announced today at a press conference that its privacy-preserving computation framework “Secret Flow” has been made open-source for developers in the globe. Secret Flow was developed by Ant Group 6 years ago, with security and openness as the core design concept, covering almost all the current mainstream privacy computing technologies.
When put to used, the framework can effectively lower the technical threshold for developers' applications and can help applying privacy computing to AI, data analysis and other fields, solving the technical pain points of privacy protection in the industry, according to Ant Group.
The framework is now available for free access through GitHub, Microsoft's collaborative code development platform and Gitee, a Chinese Github alternative founded in 2013 by Shenzhen-based Open Source China.
Ant Group’s press conference was supported by the Privacy-Preserving Computing Alliance of China Academy of Information and Communications Technology (CAICT) and attended by multiple experts from Chinese Academy of Sciences, China Banking Association, and China Computer Federation.
Tang Weiqing, Secretary General of the Chinese Computer Federation, and Wei Tao, Vice President and Chief Technical Security Officer of Ant Group, jointly announced the establishment of “CCF-Ant Privacy Computing Special Research Fund”, dedicated to building a platform for industry-academia-research cooperation.
According to experts who spoke at the conference, the industry generally believes that in 2022, regardless of policy requirements or technical maturity, the data industry will bid farewell to the era of plain text and enter the era of data privacy, and data circulation must be carried out under the premise of security assurance and personal privacy protection. Privacy computing is considered to be the key technology to achieve said visions.
In 2020, China’s State Council recognized "data" as a key factor of production, in a opinion statement, which was intended to promote the openness and secure and efficient sharing of data and enhancing the value of social data resources.