Original technology cloud report.
In the past two years, privacy computing has gradually become known to the public from a niche field. In 2021, privacy computing will begin to be fully implemented in real business scenarios.
According to the "2021 Privacy Computing Industry Research Report" released by KPMG, driven by the dual needs of big data integration applications and privacy protection, the domestic privacy computing market will develop rapidly, and technical service revenue is expected to reach 10 billion to 20 billion in three years. Metaspace will even leverage the operational income of hundreds of billions of data platforms.
Such a large market space has attracted many manufacturers to enter the market. Domestic Internet giants such as Ant, Tencent, and Baidu have laid out relevant tracks, and a large number of start-ups have also emerged in the market.
At what stage has privacy computing reached today? What changes have taken place in the domestic privacy computing market? What other challenges hinder the large-scale application of private computing?
Big and small giants are pouring into the track, and the demand for privacy computing is booming
In the eyes of keen capital, the privacy computing market derived from big data and blockchain technology has become a new track in 2021.
Thanks to the gradual improvement of data security and privacy protection legal systems around the world, as well as ideological innovation and technological breakthroughs related to privacy computing, privacy computing is becoming a standard feature of the digital economy, and thus has become a very good choice in the field of data applications. Investment track.
Judging from the investment and financing situation, the financing activity in the entire privacy computing field is very high. According to incomplete statistics from the Zero-One Research Institute, as of the end of September 2021, privacy computing startups have received a total of 63 equity financings, and the total annual financing exceeded 6 billion.
According to Zero One Finance's "Opening a New Era: Privacy Computing Application Development Report in the Financial Sector (2021)", from the perspective of players entering the market, there are a large number of privacy computing companies involved in the market, which can be roughly divided into 10 categories. Among them, start-ups in the field of privacy computing Companies are probably the most active and there are many of them.
The first category is Internet giants.
Internet giants such as Alibaba, Ant Group, WeBank, Tencent Group, Baidu Group, Huawei Group, JD.com, ByteDance, etc. have begun to make efforts in the direction of privacy computing, and many of their business sectors have launched privacy computing products. .
The second category is cloud service providers.
Cloud service providers such as Alibaba Cloud, Tencent Cloud, Baidu Cloud, JD Cloud, Kingsoft Cloud, Huawei Cloud, and UCloud have all launched privacy computing services.
The third category is companies with artificial intelligence background.
For example: Ruilai Wisdom, Yiduyun, Three-Eyed Elf, Yuanting Technology.
The fourth category is companies with blockchain background.
For example: Matrix Element, Oasis, ARPA, Qulian Technology, Lingyao Universe, Yulian Technology, Yifan Digital, Yizhi Technology, Arithmetic Force, Tongji Blockchain, etc.
The fifth category is companies with a big data background.
For example, Starlink Technology.
Category 6: Companies with security background.
For example: Alibaba Security, Tencent Security, Baidu Security, Anheng Information, China Rongan, Pingbo Technology, Shahai Technology, etc.
Category 7: Software service providers.
For example: Puyuan Information, Shenzhou Taiyue.
Category 8: Companies with financial technology background.
For example: Tongdun Technology, Bairong Yunchuang, Fushu Technology, Tianmian Technology, Jinzhita Technology, Bingjian Technology, Tiancheng Finance, etc.
Category 9: Companies with supply chain finance background.
For example: Lianyirong, Zhigui Technology, etc.
Category 10: Start-ups starting from privacy computing.
For example: Huakong Qingjiao, Nebula Clustar, Shudou Technology, Blue Elephant Intelligence, Insight Technology, Nuwei Technology, Yifangjianshu, Impulse Online, Light Tree, Rongshu Lianzhi, Molian Technology, Mirror Technology, Shenpu Technology, Homomorphic Technology, Kaixin Technology, Xinchen Shuzhi, etc.
The prosperity of the privacy computing market is not only reflected in the explosive growth in the number of manufacturers on the track, but also in its application. At this stage, privacy computing has reached the point where it can be commercially used.
Judging only from the number of companies participating in the privacy computing product evaluation and testing of the China Academy of Information and Communications Technology, 88 companies have successively released privacy computing technology-related products; and from the perspective of the number of products, compared with 15 in 2019, 2020 There are 54 models, and the number of products this year has reached 105, which is more than doubling every year.
In addition to the doubling of the number of products, the proportion of privacy computing products that have entered the implementation and deployment stage has also been increasing year by year. According to statistics from the China Academy of Information and Communications Technology, there were basically no actual deployed privacy computing applications in 2018 and 2019, but there were 38% in 2020 and 48% in 2021. This means that many products today can support larger-scale Application deployment.
In terms of application scenarios, the financial industry has become the most important industry in the field of privacy computing applications. Banks, insurance and other large institutions are constantly increasing their investment in the research and application of privacy computing technology, and use privacy computing in risk control, marketing and other scenarios. Carry out business innovation.
In addition, the government applications of privacy computing have increased. More and more local governments are building their own data capability open platforms, hoping to empower the development of the local real economy through their own data openness. How to protect data security during the open process? There has been a strong demand for privacy and privacy, and privacy computing technology has begun to be introduced.
For example, some cities in Jiangsu and Zhejiang have now realized the sharing of government data and bank financial data through privacy computing technology, and have actively used these data in anti-fraud work. There are also government agencies that want to procure privacy computing modules during tenders.
Three major technical challenges: Privacy computing faces difficulties in large-scale promotion
Although private computing has become a golden track for giants big and small to compete for deployment, the development of the field of private computing is still in its early stages, the technology is not fully mature, and the business is still in the exploratory stage.
According to the "Privacy Computing White Paper (2021)" released by the Privacy Computing Alliance and China Academy of Information and Communications Technology Yunnan University, privacy computing technology is in a stage of rapid iteration and development, and there are still many challenges in terms of privacy computing security, performance and data interconnection. There are challenges.
In terms of security, algorithm protocol security, development application security, and security consensus have become challenges faced by the current promotion and application of privacy computing.
Since privacy computing products are different from other data processing products and have the important function of protecting private data security, both technical service providers and enterprise customers should treat security challenges with caution.
Taking algorithm protocols as an example, absolute security cannot yet be achieved. On the one hand, the algorithm protocols of privacy computing products are highly differentiated, making it difficult to form a unified algorithm security foundation. On the other hand, the security protocols of privacy computing products rely on security assumptions, which poses security risks. .
In terms of performance, performance bottlenecks hinder the large-scale application of privacy computing.
In the process of implementing privacy computing, a huge cost of computing power has to be paid. This is because ciphertext calculation requires greater computing and communication loads, and the synchronization and availability of privacy calculations also require higher resources from privacy calculation participants, causing privacy calculations to encounter performance bottlenecks. How to empower privacy computing through computing power acceleration technology must be considered.
In terms of data interconnection, it is difficult to complete information interaction between different privacy computing platforms, which may turn "data islands" into "data islands".
Since privacy computing covers a variety of algorithm principles, there are interconnection challenges in protocol connections; at the same time, the diversity of functional components in the system design process also increases the cost of interconnection. Ultimately, whether various privacy computing platforms can form a unified tool depends on different scenarios, different segments and tracks.
From the perspective of business model, most companies have not yet formed a mature business model. Among domestic enterprise financing rounds involving privacy computing this year, the number of financings in the early stage (Series B and before) accounted for 81%, which also means that the commercialization of privacy computing is still in the exploratory stage.
In the future, with the further integration of privacy computing technology and blockchain technology, the development of open source, and the continuous enrichment of application scenarios, more business models may emerge.
Conclusion
As the only technical solution to promote data interconnection between enterprises, privacy computing technology has huge commercial value. From the perspective of industry development maturity, the domestic privacy computing market has just started, and all applications are being tried and explored. If last year was the first year of privacy computing technology, then this year is undoubtedly the first year of commercial implementation. The long journey of privacy computing has just begun.
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