So what kind of technology is privacy computing? Why is it so important? It originally originated from a "millionaire" idea proposed by Academician Yao Qizhi in 1982, which was used to solve the problem of trusted computing in the case of data opacity. Together with artificial intelligence, etc., it has become an emerging technology in the era of data elements, and it plays an increasingly important role in social development.
Privacy computing has become important because its underlying component—data, has become a factor of production and has begun to promote the development of social production. In April of this year, the "Opinions of the Central Committee of the Communist Party of China and the State Council on Building a More Complete System and Mechanism for the Market-oriented Allocation of Factors" (referred to as "Opinions") was officially announced, and for the first time characterized the data as the fifth largest production besides land, labor, capital, and technology. element.
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The key to the leap from Web2.0 to Web3.0 is data privacy, and data ownership must truly return to individuals
A notable feature of the Web 2.0 era represented by BAT is interactivity, that is, the introduction of Web applications. It allowed users to write and read data, and introduced video streaming and online gaming, making data usher in the first real explosion. However, the Web 2.0 era does not pay enough attention to user privacy data or lacks effective solutions, making user privacy cheap and becoming a tool for large companies to exploit users.
For example, 2 years ago, Robin Li of Baidu made a statement of "trading privacy for convenience", which means that Chinese users are not so sensitive to privacy. If privacy is traded for convenience, in most cases they are willing. And this is not an isolated case in the Internet era. Before Li Yanhong’s remarks, there were a lot of financial lending products represented by ezubao, which crazily induced users to upload personal information by means of receiving cash upon registration.
For users, the long-term leakage of privacy is caused for the benefit of the moment. When this kind of behavior in the market becomes more and more frequent, sacrificing privacy is not a personal problem of users.
Therefore, an environment and mechanism to protect data security and privacy must be established, not only in legislation, but also in technical solutions. The first is legislation. In September 2018, the Standing Committee of the Thirteenth National People's Congress announced the legislative plan for the "Data Security Law of the People's Republic of China". It is also under intensive development.
On October 17, the 22nd meeting of the Standing Committee of the 13th National People's Congress closed. The meeting reviewed the draft Personal Information Protection Law. The draft stipulates that if the violation of the rights and interests of personal information is serious, the illegal income shall be confiscated, and a fine of less than 50 million yuan or less than 5% of the previous year's turnover shall be imposed. The strictest EU (GDPR). Next is business and technology. Enterprises are represented by Apple. In the latest 14.0 system, Apple has added IDFA and clipboard functions, allowing users to firmly hold data ownership in their own hands. It has also become Apple’s highest level of protection for user privacy data. In terms of technology, privacy computing, as an emerging technology, has ushered in rapid development in recent years.
As mentioned above, this technology was originally proposed by Academician Yao Qizhi to solve the idea of "millionaires": when two millionaires meet on the street, they both want to know who is richer, but they don't want to let the other party know. With the real wealth you own, how can you let the other party know who is richer without a third party? That is, how to solve the trusted computing problem in the case of data opacity.
Generally speaking, there are currently two mainstream methods to solve this kind of problem: one is to use cryptography + distributed system method, but it is ideal and the cost is higher; the other is to use hardware solutions, by implementing a hardware trusted third party ( trusted third party, TTP), to receive input and output of private data from multiple parties, that is, Trusted Execution Environment (TEE for short).
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Protecting data privacy does not mean becoming an "isolated island", blockchain + privacy computing helps data flow safely and freely
However, the current privacy computing solution is not mature enough, and there is still a serious island effect in the data market. On the one hand, the need to protect the privacy and security of personal and institutional data does not mean that the data is closed; on the other hand, the application of various aspects of society urgently needs the value of multi-party data, and data needs to become a real factor of production to flow and drive social development. .
Whoever can solve this problem will get a huge track. Therefore, a group of cutting-edge entrepreneurs began to emerge in this field, such as former Google engineer Yin Hang and former Tencent product manager Tong Lin. They abandoned the traditional "coin circle" method of publishing public chains, but designed a system based on the well-known cross-chain protocol Polkadot, Phala Network, which supports heterogeneous cross-chains and allows privacy smart contracts to interoperate. They said that traditional TEE privacy computing schemes rely too much on hardware facilities, so there are some inherent defects: it is difficult for hardware privacy computing schemes to solve the problems of availability and state consistency at the same time. The so-called availability means that the private computing device cannot continue to provide services in case of an emergency (such as power outage); and the state consistency means that when multiple trusted computing nodes have interactive requirements, the order of code execution is unclear, which will lead to conditional competition. .
Therefore, it is necessary to seek new technical support in addition to hardware. In addition, the traditional TEE solution also has inherent disadvantages on two levels. First, it cannot achieve interoperability (combinability of smart contracts, cross-platform interaction, etc.), and it has formed a conflict among privacy computing vendors under the condition of solving local data islands. New silos; second lack of motivational effect. The goal of privacy computing is to realize data flow under the premise of ensuring data privacy and security, that is, trusted computing. But a premise that is easily overlooked is whether the supply and demand of data match, that is, whether there are enough credible computing requirements on the data of a given scale.
Blockchain is the optimal solution to make up for these disadvantages. On the one hand, the distributed characteristics ensure the safety and reliability of data, and return the ownership and usage rights to users; Solve the problem of data confirmation and pricing, so that all individuals can enjoy the dividends of data, thereby activating the transaction momentum of the entire data market.
Yin Hang, who has 4 years of experience in blockchain design, believes that Phala Network, which adopts the TEE-blockchain hybrid architecture, can make TEE computing out of the blockchain. There are hardware defects, and smart contracts also need to be composable to produce economies of scale. Therefore, the Phala protocol is committed to realizing the confidential computing and composable interaction of smart contracts, and using the power of blockchain to help private computing become the optimal solution to protect commercial secrets.
Based on the above logic, this open, non-permissioned privacy computing blockchain can be downloaded by anyone without permission by encrypting and storing state data on the chain. Using the NPos consensus algorithm, each node can get a consensus status. At the same time, in order to achieve composability, Phala Network has learned Polkadot's cross-chain communication protocol, introduced a unique layering and event traceability mechanism, separated contract reading and writing, and allowed contracts to communicate with each other, even with external blockchains. operate.
Mr. Zhang Yingchun, VP of Solution Architecture of Lighttree Technology, a multi-party security computing manufacturer, said in an interview with the computing power think tank: the combination of privacy computing technology and blockchain technology is based on the perspective of "physical dispersion and logical concentration" of data. Fundamentally balance the contradiction between data security and data value. This is where the value of privacy computing is most recognized.
According to the latest forecast data from IDC, the overall revenue of China's big data-related market will reach US$10.42 billion in 2020, a year-on-year increase of 16.0% over 2019, while the overall revenue of the global big data-related hardware, software, and service markets will reach US$187.84 billion . Since 2014, China's first big data exchange has settled in Guiyang. A few years later, Wuzhen and Shanghai also established big data trading centers and exchanges.
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Under the stricter global data regulation, new solutions are needed for cross-border data flow
Last month, The Wall Street Journal reported that the Irish Data Commission had ordered Facebook to suspend the transfer of data of its EU users to the US. On the other hand, the United States has also continued to attack TikTok, requiring it to reach a sale plan to the United States within a specified time, and the Chinese Ministry of Commerce and the Ministry of Science and Technology have also adjusted the import and export technology catalog, which means that ByteDance needs to sell TikTok. Obtain state license.
On the one hand, these incidents show that data security has become a national strategy and an international issue; on the other hand, it also shows that under the new stricter data regulation and complex international situation, companies engaged in data cross-border activities need to reconsider their underlying architecture design , to avoid being unable to guarantee self-data transmission and computing services when the international situation deteriorates.
The EU has arguably the strictest data protection laws in the world. In April 2016, the European Union promulgated the "General Data Protection Program" (GDPR), which stipulates that the consequences of non-compliance with data privacy regulations will be subject to severe sanctions and huge fines. The maximum limit can reach 20 million euros or the previous financial year. 4% of the annual operating income, whichever is greater.
Dr. Ran Yang from the privacy computing network PlatON said that for cross-border companies, if they want to comply with the ruling of the EU Supreme Court on data security, it means that their own data infrastructure must be redesigned. "This design is not for distribution, but for dividing and storing data about European users." That is to say, it is pure data high-pressure supervision. On the other hand, most privacy computing service providers are based on TEE computing, and the core hardware of TEE is CPU, which is monopolized by Intel. Therefore, it means that under the strict data supervision and complex international situation, there is still the risk of being cut off by the giants and doing evil.
Therefore, it is necessary to find a thorough privacy computing solution to avoid the risk of high-pressure supervision and giants doing evil. In this case, the permissionless privacy computing services of protocols such as Oasis labs and Phala Network show their own advantages. Unlike most current TEE-based privacy computing vendors, TEE trusted computing nodes such as Phala come from all over the world and are a permissionless privacy computing service.
The advantage of permissionless privacy computing services is that computing nodes are distributed all over the world and can enter and exit freely, avoiding the risk of being blocked. For example, for the problems often encountered in such traditional privacy computing, non-permissioned blockchains also show advantages: Yin Hang and Tong Lin designed Phala Network to support multiple TEE standards, including Intel SGX, AMD SEV or ARM TrustZone and other standards; and due to cross-chain interoperability, Phala Network can provide confidential contracts for any blockchain.
Therefore, in the new era, TEE-non-permissioned blockchain architecture solutions (such as Oasis Labs, Phala Network, etc. mentioned above) may be more meaningful. Andrey Sergeenkov, the founder of Btcpeers.com, said in an article on the well-known overseas developer blog Hackernoon the day before yesterday, "The power of the blockchain network is inherent. Technically speaking, it is unlikely that the decentralized network will be banned." , just like it has been since the creation of the Bitcoin network 12 years ago. Similarly, although the TEEs operated by individual chip manufacturers can be recycled or manipulated, the TEE clusters spread all over the world on the distributed computing network can never be controlled or shut down. Even At the same time, in order to eliminate any possible backdoors, PhalaNetwork uses the "random miner" mechanism to randomly assign tasks to TEE so that attackers (banners) cannot create backdoors for specific TEE chips, thereby ensuring the stability of privacy computing services .”
