China National Series of Standards for Privacy-Preserving Computation Released, Leading Enterprise ARPA Assisted

Recently, the Big Data Industry Conference 2020, hosted by the China Academy of Information and Communications Technology (CAICT) and China Communications Standards Association (CCSA) was held in Beijing. The big data team of CAICT released a new set of standards to guide data circulation.

A series of privacy-preserving computation standards devised by CAICT and developed by Ant Financial Services, WeBank, Tencent Cloud, Baidu, Intel, ARPA and other companies, were formally released at the conference. They included the recently published, “Technical Requirements and Test Methods for Data Circulation Products based on privacy-preserving multi-party computation (revised edition)” and “Technical Requirements and Test Methods for Data Computing Platforms Based on Trusted Execution Environments.

With the big data industry’s market share expanding rapidly, the open sharing, exchange, and circulation of big data has become a trend. It can be said that data circulation is the key to releasing data value. However, data circulation is also accompanied by many issues like ownership, quality, compliance, and security. These have become bottlenecks restricting data circulation.

In order to solve these problems, big data practitioners have been looking at them from different perspectives. So far, the exploration from a technical perspective is fruitful and promising. The privacy-preserving computation technology, represented by privacy-preserving MPC and trusted execution environment, provides inspiring solutions to the problems that occur in data circulation and has become an important breakthrough in the big data industry in the past two years.

However, several questions remain unanswered. Are the existing laws and regulations suitable for the technology? What will the future of privacy-preserving computation technologies and related laws and regulations be like?

The theme of this year’s Big Data Industry Conference was “Data circulation and privacy-preserving computation.” Participants discussed possible solutions from both the technical and legal perspectives. Experts from CAICT introduced the Big Data Technology and Standard Committee (TC601) of the China Communications Standards Association (CCSA). They explained their progress in formulating and revising the standards of privacy-preserving multi-party computation (MPC), trusted execution environment, federal learning and other series of standards.

At the same time, they also gave an in-depth interpretation of the highlights of the second batch of privacy-preserving multi-party computation (MPC) product testing and analyzed its development trend. What’s more, experts from leading privacy-preserving computation companies and senior experts engaged in related legal research discussed the relevant technical and legal issues.

The development and revision of standards is led by the Big Data Technology and Standard Committee of the CCSA, which is mainly concerned with the privacy protection and data circulation compliance scenarios involved in the data circulation process, targeting the two technologies of privacy-preserving multi-party computation (MPC) and trusted execution environment.

As a scientific research institution directly under the Ministry of Industry and Information Technology, the China Academy of Information and Communications Technology (CAICT) is a national specialized think tank and is responsible for uniting enterprises in the industry to promote industry innovation and development. It plays an important role in developing major strategies, policies, standards and test accreditation in communications, cloud computing, big data and other industries.

ARPA also participated in the development of the original version of the standard, which was revised for the first time by the project team. This revision adds new test cases such as multi-party security fault tolerance and upgrade support, increases the number of mandatory test items, and streamlines and consolidates the original test cases. Overall, the technical architecture has been updated and the technical threshold has been raised to better adapt to industrial development.

In the trusted execution environment standard, the project team standardized common terminology, technical architecture and security model, and standardized product capabilities from nine perspectives, including task processing capability, algorithm scalability, environment validation, communication security, computing confidentiality, consistency, data storage, auditing, operation and maintenance.

ARPA is a leader in secure multi-party computing (MPC) technology. With MPC, operations can be performed on encrypted data, making the data available for analysis but remains invisible and secure. ARPA helps different organizations conduct data sharing, model training and prediction while meeting the requirements of user privacy protection, data security policies and regulations. Shared learning technology has been applied to various business scenarios such as credit, risk control, insurance, and government affairs.

In 2019, the “Standard for Data Circulation Products Based on Secure Multi-party Computation” (the Standard), led by the China Academy of Information and Communications Technology, was officially released. Also involved in the process were Ant Financial, Baidu Security, Ali Security and other notable institutions. ARPA was deeply involved and directly led the compilation of multiple contents of the cryptographic protocol level in the Standard, and provided a large number of opinions and suggestions on the theoretical and product aspects of secure MPC. At the same time, ARPA has reached a long-term deep cooperative relationship with China Information and Communication Research Institute.

2019 December, ARPA was invited by IEEE (Institute of Electrical and Electronics Engineers) to participate in developing the IEEE Standard for Technical Framework and Requirements of Shared Machine Learning (IEEE P2830).

The standard aims to standardize the definition of shared machine learning, technical framework, technical process, technical characteristics, security requirements, etc., on an international level.

The IEEE Shared Machine Learning Standard is a standard led by Ant Financial Services Group (formerly known as Alipay, is an affiliate company of the Chinese Alibaba Group. Ant Financial is the highest valued FinTech company in the world, and the world’s most valuable unicorn company, with a valuation of $150bn). Companies and research institutions such as ARPA, Zhejiang Financial Technology Association, Zhejiang Standardization Research Institute, China Electronics Standardization Research Institute, Alibaba, Lenovo, China Mobile, Zhejiang University, and other research institutions participated.

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 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 with each other 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 proof-of-concepts and MPC products. In 2019, ARPA was named as the Top 10 most innovative blockchain companies in China by China Enterprise News and China Software Industry Association.

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ARPA is a privacy-preserving blockchain infrastructure enabled by MPC. Learn more at

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ARPA is a privacy-preserving blockchain infrastructure enabled by MPC. Learn more at