ARPA Co-authored “Privacy-Preserving Computation White Paper (2021)” Officially Released

One of the digital economy era characteristics is that data is treated as the key production factor through inter-organizational data circulation across fields, industries, and regions. However, while facing the need for data fusion, how to prevent data leakage, misappropriation and abuse is still a challenging problem faced by institutions when participating in data circulation.

Driven by policies and market demands, privacy-preserving computing technology, industry, and applications have developed rapidly in the past two years. Privacy-preserving computation has become an important method to realise the circulation of data and in-depth data value mining under the premise of protecting the rights and security of data owners and personal privacy.

In 2021, as one of the main authors, ARPA jointly completed the “Privacy-Preserving Computation White Paper (2021)” with more than 40 enterprises from the China Academy of Information and Communications Technology Cloud Institute and the Privacy-preserving Computing Alliance. This white paper was officially released at the “2021 Privacy-preserving Computing Conference” on July 20. The white paper presents the development of privacy-preserving computation from a panoramic view of policies, technologies, industries, applications, and legal compliance. It hopes to provide reference and guidance for applying privacy-preserving computing technology in the industry, promote the healthy development of the privacy-preserving computing industry, and make privacy computing play a more excellent value in constructing the data element market and data circulation process.

This white paper mainly attempts to answer the following questions:

● What is Privacy-preserving computation: What brings privacy-preserving computing technology? What value does it get? What kind of policy environment does it face?

● Development of privacy-preserving computing technology: what is the technical system of privacy-preserving computation? What are the scheme architectures and characteristics of various privacy-preserving computing technologies? What are the problems that each privacy-preserving computing technology is good at solving? What are its maturity and weaknesses? What is the status of technology integration and expansion?

● Privacy-preserving computing application scenarios: What are the commonly used application scenarios for privacy-preserving computing? In each scenario, what pain points do privacy-preserving computing address, and how does it apply?

● Development of the privacy-preserving computation industry: what are the leading players at home and abroad? What is the market structure? What is the business model, investment and financing situation, patent situation, paper publication situation, technology open source situation, and standard construction situation of the privacy computing industry?

● Privacy-preserving computing compliance: From a legal perspective, what compliance issues does privacy-preserving computation solve for data circulation? What compliance risks are faced in the process of applying privacy-preserving computing? How to address these risks?

●Issues and Challenges: What are the issues facing the development of privacy-preserving computing? How can these problems be improved?

The person in charge of the Cyber Security Administration of the Ministry of Industry and Information Technology believes that privacy-preserving computing technology has proposed an innovative solution to the critical problems of personal privacy protection, data security risks, and data silos. Privacy-preserving computation has become one of the crucial ways to balance data utilisation and security.

At present, China’s privacy-preserving computation technology has a good foundation for development in terms of the policy environment, technology system, and industry situation. ARPA will continuously focus on supporting the acceleration of the development and application of key technologies, promoting the construction and improvement of the standard system, and guiding the industry’s orderly and standardised high-quality development.

About ARPA

ARPA is a blockchain-based solution for privacy-preserving computation, enabled by Multi-Party Computation (“MPC”). Founded in April 2018, the goal of ARPA is to separate data utility from ownership and enable data renting. ARPA’s MPC protocol creates ways for multiple entities to collaboratively analyze data and extract data synergies while keeping each party’s data input private and secure. ARPA allows secret sharing of private data, and the correctness of computation is verifiable using the information-theoretic Message Authentication Code (MAC).

Developers can build privacy-preserving dApps on blockchains compatible with ARPA. Some immediate use cases include: credit anti-fraud, secure data wallet, precision marketing, joint AI model training, key management systems, etc. For example, banks using the ARPA network can share their credit blacklist for risk management purposes without exposing their customer data or privacy.

Team members have worked at leading institutions such as Google, Amazon, Huawei, Fosun, Tsinghua University, Fidelity Investments. ARPA is currently assisting the China Academy of Information and Communications Technology in setting the national standard for secure multi-party computation. ARPA is a corporate member of MPC Alliance and IEEE and is in partnership with fortune 500 companies to implement proofs-of-concept and MPC products. In 2019, ARPA was named the Top 10 most innovative blockchain companies in China by China Enterprise News and China Software Industry Association.

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