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Development Report on Privacy Computing Technology: Opening the Door to Privacy under the Value of Data



At present, emerging technologies such as big data, cloud computing, Internet of Things, artificial intelligence, and blockchain are constantly emerging, and the wave of digital economy is sweeping the world, becoming a new driving force for economic growth in a new round of technological revolution and industrial transformation. With the vigorous development of the digital economy, data is gradually getting rid of the original simple digital symbols and transforming into a new generation of production factors after land, energy, population, and food. As a mapping window between the real world and the digital world, it contains The huge value has become a key part of the digital economy.

However, compared with the continuous recognition of the value of data applications, the issue of data privacy has become increasingly prominent, and the issue of how to protect user data privacy needs to be resolved urgently. Industry insiders believe that privacy computing is the "key" to solving this problem.

In recent years, mainstream technology research on privacy computing has sprung up like mushrooms. All parties start from certain technical means of privacy computing to discuss the technical feasibility and the improvement of existing performance, but systematic technical research reports are still rare. In this context, the "Privacy Computing Technology Development Report" was jointly published by Sina Finance, Securities Daily, and Shenzhen Information Service Industry Blockchain Association, written by Matrix Element and Gyro Research Institute. The report addresses privacy from both market and technical aspects. Computing conducts an in-depth analysis, and presents the panorama of privacy computing from multiple dimensions such as the development of privacy computing, introduction of mainstream privacy computing technologies, technical project introduction, and application scenarios of privacy computing, and explains in detail the opportunities and challenges of privacy computing in the digital age. It aims to attract more technology enthusiasts to participate in the technical exchange of privacy computing, and at the same time let the public have a clearer understanding of privacy computing technology, and promote the application of privacy computing technology in cloud computing, Internet of Things, artificial intelligence, and blockchain. technology applications.

Coinbase launched the privacy computing network Oasis (ROSE): On April 26, Coinbase launched the privacy computing network Oasis (ROSE), and deposits are now open. Subject to liquidity conditions, trading will begin on or after 9AM PT on Tuesday, April 26, with a phased launch of the ROSE-USDT trading pair. [2022/4/26 5:11:15]

The following are the highlights of the report:

The integration of privacy computing and high-tech brings "four advantages" and a bright market prospect

In the context of the gradual digitalization of society, the key role of private computing technology is emerging. According to the Statista report, the revenue of the global big data market will reach US$56 billion in 2020, twice that of 2016. In the future, the big data market will show a trend of steady development, and the growth rate is expected to reach about 14%. In the 2018-2020 revenue forecast period, Statista predicts that it will maintain an annual growth rate of about 7 billion US dollars, with an average annual compound growth rate of about 15.33%.

WeBank's public big data privacy computing platform WeDPR-PPC: According to official news, on May 26, WeBank's WeDPR-PPC multi-party big data privacy computing platform based on blockchain technology was unveiled at the Guiyang China International Big Data Industry Expo (referred to as Data Expo) to provide innovative solutions to ensure data availability and privacy in privacy computing. At the same time, FISCO BCOS, the financial-grade blockchain underlying open-source platform developed by the Golden Chain League open-source working group led by WeBank, won the Leading Technology Achievement Award at the 2021 Digital Expo.

It is reported that ISCO BCOS is a financial-grade blockchain underlying open source platform led by WeBank and jointly created by the Open Source Working Group of the Golden Chain Alliance. It was officially open sourced in 2017. FISCO BCOS has brought together 2,000+ enterprises and 40,000+ developers to participate in ecological co-construction, supporting the research and development of hundreds of application projects, of which more than 120 applications have been put into use, covering cross-border mutual recognition of health codes, government affairs, regulatory technology, Business scenarios such as social governance and copyright protection. [2021/5/26 22:46:56]

AntChain Privacy Computing Platform Passed All Evaluations by the Academy of Information and Communications Technology: Jinse Finance reported that the big data product evaluation of China Academy of Information and Communications Technology has been updated again. According to the evaluation results recently released by China Academy of Information and Communications Technology, a total of 106 products from 49 companies have passed Among them, the AntChain data privacy service is the only platform that has passed the comprehensive ability assessment in this round. In order to further improve data ownership issues, data sharing, smart contract technology, collaborative computing, etc., the Institute of Information and Communications Technology also led the establishment of the "Privacy Computing Alliance".

According to the Institute of Information and Communications Technology, the AntChain data privacy service is the only platform that has passed the comprehensive capability assessment in this round, and has also become one of the first members of the "Privacy Computing Alliance" of the Institute of Information and Communications Technology.

It is reported that the data privacy service developed by AntChain integrates a blockchain-based digital identity and authorization system, supports trusted programming of data privacy calculation steps and multi-party collaboration logic, lowers the threshold of privacy computing technology, and enhances collaborative governance of privacy computing , The technical capability of credible auditing, and the technical capability of providing full life cycle protection for private information. [2020/12/21 15:58:23]

Source: "Big Data White Paper (2019)"

From the analysis of digital identity, the main application of privacy computing, the market size of privacy computing is still not to be underestimated. According to the latest report from the intelligence and market research platform MarketsandMarkets, the global digital identity solutions market size reached US$13.7 billion in 2019, and is expected to grow to US$30.5 billion in 2024, with a compound annual growth rate of 2019-2024. rate (CAGR) of 17.3%.

Justin Sun: In 2020, TRON will launch the 4.0 upgrade, which will introduce privacy computing, PBFT one-click chain issuance and other technologies into TRON: At 15:00 on August 5, the third live broadcast of the 2020 Smart Cloud Summit will officially start. This cloud conference Titled by Metaverse DNA, co-hosted by Ant Node Alliance and Jinse Finance, the theme is "DeFi leads the forefront of digital finance".

Sun Yuchen, the founder of TRON, first reviewed the birth of top companies and companies in the industry such as TRON, Binance, and Jinse Finance at the Fanzhi Summit in 2017. Three years have passed, and in 2020, TRON launched a strong upgrade of 4.0, introducing the world's latest technologies such as privacy computing, enterprise-level services, PBFT one-click chain issuance, and cross-chain into the TRON blockchain. At the same time, TRON entered the DeFi Strong progress has been made, and finally he congratulated the success of the 2020 Smart Summit. [2020/8/5]

The report pointed out that privacy computing can be combined with artificial intelligence, blockchain, big data and other high-tech technologies, and technology selection can be carried out according to specific application scenarios to solve practical problems. It brings four very significant advantages.

Use: Improve the ownership of personal data and realize the use of data under the authorization mechanism.

Security: reduce the risk of enterprise data leakage, and fundamentally solve the problem of data leakage caused by the direct collection of user information by enterprises

News | The decentralized privacy computing solution ZEXE officially established a code base on Github: The new decentralized privacy computing solution ZEXE officially established a code base on Github. The ZEXE scheme was proposed by researchers Sean Bowe (Zcash), Alessandro Chiesa (UC Berkeley), Matthew D. Green (Johns Hopkins University) and others through the paper "Zexe: Enabling Decentralized Private Computation", using zero-knowledge Cryptographic knowledge such as proof and recursive proof synthesis can realize efficient off-chain calculation and on-chain verification under the premise of protecting data privacy. The program is currently in the academic proof-of-concept stage. [2019/4/7]

Monetization: Drive the realization of user data, meet the multi-party data sharing under the premise of privacy protection, and obtain corresponding economic incentives.

Flow: Facilitate institutional data flow, break down "data islands", and maximize the value of enterprise and institutional data.

Privacy computing "schools" Many cryptography is the core engine driving privacy computing technology

The report pointed out that from the perspective of technical theory, privacy computing is mainly divided into three major technical routes, namely cryptography, trusted execution environment, and federated learning.

Cryptography is a privacy computing technology represented by Secure Multi-party Computation, Homomorphic Encryption, and Zero-knowledge Proof.

The Trusted Execution Environment (TEE) uses hardware technology to isolate and protect data and classify data. In a CPU that supports TEE, there will be a specific area, which is used to provide a more secure space for the execution of data and codes, and to ensure their confidentiality and integrity.

Federated learning is an emerging artificial intelligence technology that has emerged in recent years. It was first proposed by Google in 2016. Its design goal is to ensure information security during big data exchange, protect terminal data and personal data privacy, and ensure legal compliance. Under the premise of , carry out efficient machine learning among multiple participants or multiple computing nodes.

It is undeniable that although there are differences in privacy computing technology routes, cryptography still plays an important role in privacy computing, and the research results of cryptography theory also affect the progress of privacy computing technology.

Data privacy protection laws are increasingly sound, and technical specifications are a necessary prerequisite for industry development

The report mentioned that privacy computing, as a technology aimed at data security, has high technical complexity and involves a wide range of industries. The degree of data governance and standardization is the key to the long-term development of technology.

In recent years, with the public's increasing emphasis on privacy, a series of laws and regulations have been issued around the world for data privacy protection, and the legal system has become increasingly sound and standardized. On the international front, in addition to the well-known General Data Protection Regulation (GDPR), the International Organization for Standardization ISO has issued a series of related standards and specifications, including ISO/IEC 29100 "Privacy Protection Framework", ISO/IEC 29101 " Privacy System Architecture", ISO/IEC 29190 "Privacy Capability Assessment Model", ISO/IEC 29134 "Privacy Impact Assessment", ISO/IEC29151 "Personally Identifiable Information Protection Guidelines".

Domestically, the "Network Security Law of the People's Republic of China" implemented in 2017 emphasizes the protection of infrastructure and personal information. The "Information Security Technology Personal Information Security Specifications" implemented in 2018 clarifies the compliance requirements for enterprises to collect, use and share personal information from the perspective of national standards. In July 2020, the Shenzhen Municipal Bureau of Justice promulgated the "Shenzhen Special Economic Zone Data Regulations (Draft for Comment)", which is the first government document to implement data as a factor of production. It has strong symbolic significance and extremely high value. Recently, the "Data Security Law of the People's Republic of China (Draft)" ended the solicitation of opinions. The draft clarified the data security protection obligations of organizations and individuals carrying out data activities, and implemented specific measures to support and promote data security protection responsibilities.

In addition, units such as the Institute of Information and Communication Technology and the Institute of Electric Standards have also successively led the formulation of standards related to privacy computing, including "Technical Requirements and Test Methods for Data Circulation Products Based on Multi-Party Secure Computing", "Blockchain Privacy Computing Service Guide", etc.

At present, the laws and regulations related to privacy computing are still being improved. It is foreseeable that the continuously optimized top-level design and gradually standardized technical standards will spur new vitality to the privacy computing industry.

Privacy computing products are gradually entering the market to compete for commercial applications is the key

The report pointed out that many well-known privacy computing products or technical frameworks have appeared in the current market, including Rosetta, an open source framework for privacy machine learning for AI developers launched by Matrix Element; Ant Chain Moss launched by Ant Financial Multi-party secure computing platform; Baidu's general computing architecture based on trusted execution environment - MesaTEE, etc.

Commercial applications are the "sole standard" for testing product strength. Privacy computing can realize data calculation and analysis while ensuring the security and privacy of original data. There are a wide range of application scenarios in many industries such as government affairs, finance, medical care, transportation, and security.

Taking the medical and health application in the report as an example, through secure multi-party computing and other privacy protection methods, efficient data statistical analysis and even machine learning can be completed without the data leaving the private domain. In fact, in the field of biomedicine, privacy computing has gradually landed. In terms of data joint analysis, genomics data, medical imaging data, and clinical data have begun to be safely and reliably shared and calculated in some innovative projects. In addition, the use of privacy computing technology (secure multi-party computing, proxy re-encryption, etc.) to achieve cross-domain sharing of patient electronic medical records is also an effective solution to the pain points of hospital data islands.

It is foreseeable that cloud computing, mobile Internet (Internet of Things), artificial intelligence, blockchain, these technical elements and data elements are interconnected and deeply integrated, which is an inevitable trend of industrial development. In the future, with the continuous detonation of new privacy-related business needs, continuous feedback and expression from the market, the gradual establishment of a legal and regulatory system for sharing and circulation of private information, private computing and cryptography will gain new impetus and continue to evolve.


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