数据安全系列二：隐私计算行业（上篇） Data Security Series II: Report on the Privacy Computing Industry (Part 1)

"近几年，我国各个相关部门持续积极推进数据安全政策的制定与出台，不断加快数据安全的政策布局，数据安全相关法律法规密集出台。 目前我国已出台《网络安全法》、《民法典》、《数据安全法》和《个人信息保护法（草案）》四部数据安全保护的上位法，逐步完善我国数据相关立法顶层设计，为整体的数据安全治理提供基本法律框架。隐私计算是平衡数据利用和安全的重要途径。自2016年，工业和信息化部、中国人民银行、国家发改委、中央网信办、国家能源局等政府监管部门先后在相关政策文件中提到加强隐私计算相关技术的攻关和应用。在政策大力出台的监管倒逼下，全行业对于数据安全的重视程度不断提高，为隐私计算行业发展提供较大助力，推动下游的行业应用场景不断丰富。

In recent years, relevant state departments have taken active and continued actions to promote the stipulation and promulgation and speed up the arrangement of data security policies, hence a list of data security related laws and regulations have been intensively released. At present, four superior laws, including Cybersecurity Law, Civil Code, Data Security Law and Personal Information Protection Law (Draft), have been announced to improve top design of data-related legislation, providing a basic legal framework to overall data security governance. In addition, breakthroughs and application of privacy computing technology, a crucial way to balance data utilization and security, have been encouraged and underscored since 2016 in policies and documents issued by the Ministry of Industry and Information Technology, the People’s Bank of China, the National Development and Reform Commission, the Cyberspace Administration of China, National Energy Administration and other government regulatory agencies. The vigorous promulgation of policies has raised awareness of the whole industry of the importance of data security, which not only gives a boost to the development of privacy computing industry but promotes the enrichment of downstream industry application scenarios.

当前隐私计算仍处发展初期，在市场需求和资本入场的推进下进入初步爆发阶段。隐私计算的技术路径也处于高速的演进和变化状态，其中联邦学习、多方安全计算和可信执行环境是当前主流技术路径，也是当下产品化的主要方向。随政策推动，隐私计算技术市场应用广泛，政务、金融、医疗等领域抢先落地。目前，市场竞争格局中初创公司、互联网公司、金融机构齐聚，但战略打法各有不同。但整体来看，行业仍处于发展早期，技术解决方案和下游客户接受度有待进一步优化，但可预见市场有望在未来三年达到百亿甚至千亿级别。而具体哪些应用场景有望持续爆发需求？不同技术流派厂商如何发展？不同商业模式未来的市场潜力如何？行业发展将引领头部厂商走向全面综合或垂直细分化的发展？凯盛研究将在本次报告中逐一进行解读。

Nowadays, privacy computing is still in its infancy, ushering in the initial explosive period driven by market demand and capital. The technological path is therefore experiencing rapid revolution and changes, with mainstream technological path featuring federated learning, secure multi-party computation and trusted execution environment, which also represent the focuses of product. The government affairs, finance and medical field has led up the use of privacy computing technology. Throughout the market competitive landscape, startup companies, internet companies and financial institutions are vying for the market, but their strategic schemes are slightly different. Taken as a whole, the industry is in the early stage of development, technical solutions and downstream customer acceptance are expected to be further improved, but predictably it will welcome a market valued at ten or even hundred billion yuan in the upcoming three years. Under these circumstances, which specific application scenarios are expected to explode in demand? How do manufactures of different technical methods develop? What is the future market potential of different business models? Will the industry development lead top manufacturers to the comprehensive integration or vertical segmentation development? All these questions will be answered in this report.

凯盛研究TMT团队已于2021年9月28日出版《数据安全系列一：数据安全政策解读及趋势分析》,现将于2021年10月19日推出《数据安全系列二：隐私计算行业（上篇）》。本研究从业内代表企业与行业协会等相关专家访谈及公开信息搜集入手，结合案头研究和历次项目经验，深入研究隐私计算细分行业现状，对行业现状、行业背景、政策环境、技术流派、核心要素、主流厂商、产业链现状、主要服务及商业化模式进行研究，进一步分析隐私计算行业的市场空间、增量潜力、驱动因素、限制因素、行业风险乱象及未来发展趋势。在此基础上，深入研究3家代表性企业：华控清交、富数科技和翼方健数，通过发展历程、核心团队、主营产品及收入、产品迭代、核心客群、获客渠道、下游客户评价、核心竞争力、未来规划等方面着手。除目录外，PDF版正文内容共计约65页左右，适合对数据安全、隐私计算细分赛道感兴趣的机构投资者或者企业客户参考。

The Data Security Series II: Report on the Privacy Computing Industry (Part 1) will be released by Capvision TMT Research Team on October 19, 2021, following the publication of the Data Security Series I: The Interpretation of Data Security Policy and Trends Report on September 28, 2021. This report is written up by utilizing interviews with enterprise and industry association experts, public information, desk-top research and pervious project experience. Also, it conducts an in-depth study of the status quo of privacy computing industry segments, and the research on industry status, industry background, policy environment, technology approaches, core elements, mainstream manufacturers, industry chain, main services and commercialization models. It further explores the market space, incremental potential, driving factors, limiting factors, industry risks and future development trends of privacy computing industry. On this basis, a thorough interpretation of three representative enterprises, namely Huakong TsingJiao, Fudata, and BaseBit.ai, has been presented by detailing the development history, core team, main products and revenue, product iteration, core customer base, customer acquisition channels, downstream customer evaluation, core competitiveness and future planning. Excluding the content section, the report totals 65 pages, and will be most beneficial to institutional investors and corporate clients interested in data security and privacy computing industry segments.

◆?报告目录 Contents

1.?核心观点

2.?行业概况 Industry Overview

??2.1 行业发展历程 Industry development history

??2.2 行业发展背景 Industry development background

??2.3 行业政策环境 Industry policy environment

??2.4 业融资情况Industry financing conditions

??2.5 主要技术流派 Main technical methods

??2.6 技术方案核心要素 Core elements of technical schemes

??2.7 下游核心场景（政务、金融、医疗、广告）Core downstream scenarios (government affairs, finance, medicine and advertisement)

??2.8 产业链分析 Industry chain analysis

??2.9 主流厂商类型 Types of mainstream manufacturers

??2.10 市场竞争格局 Market competitive landscape

??2.11 头部厂商概况 Top manufacturers overview

??2.12 行业壁垒分析 Industry barrier analysis

??2.13 市场空间分析 Market space analysis

??2.14 增量市场空间分析 Incremental market space analysis

??2.15 限制商业化因素分析 Commercialization limiting factor analysis

??2.16 行业驱动因素分析 Industry driving factor analysis

??2.17 行业限制因素分析 Industry limiting factor analysis

??2.18 行业趋势分析 Industry trend analysis

3.?标杆企业 Representative Enterprisesr

??3.1 代表企业对比分析 Comparative analysis of representative enterprises

??3.2 华控清交Huakong TsingJiao

???3.2.1 发展历程及核心团队 Development history and core team

???3.2.2 管理层评价 Senior executive evaluation

???3.2.3 商业模式分析 Business model analysis

???3.2.4 下游商用场景分析 Downstream commercial scenario analysis

???3.2.5 营收情况分析 Revenue analysis

???3.2.6 产品更新迭代分析 Product update and iteration analysis

???3.2.7 获客模式分析 Customer acquisition model analysis

???3.2.8 下游客户评价 Downstream customer evaluation

???3.2.9 核心竞争力分析 Core competitiveness analysis

???3.2.10 未来战略规划 Future strategic planning

??3.3 富数科技 Fudata

???3.3.1 发展历程及核心团队 Development history and core team

???3.3.2 管理层评价 Senior executive evaluation

???3.3.3 商业模式分析 Business model analysis

???3.3.4 下游商用场景分析 Downstream commercial scenario analysis

???3.3.5 营收情况分析 Revenue analysis

???3.3.6 产品更新迭代分析 Product update and iteration analysis

???3.3.7 获客模式分析 Customer acquisition model analysis

???3.3.8 下游客户评价 Downstream customer evaluation

???3.3.9 核心竞争力分析 Core competitiveness analysis

???3.3.10 未来战略规划 Future strategic planning

??3.4 翼方健数BaseBit.ai

???3.4.1发展历程及核心团队 Development history and core team

???3.4.2 管理层评价 Senior executive evaluation

???3.4.3 商业模式分析 Business model analysis

???3.4.4 下游商用场景分析 Downstream commercial scenario analysis

???3.4.5 营收情况分析 Revenue analysis

???3.4.6 产品更新迭代分析 Product update and iteration analysis

???3.4.7 获客模式分析 Customer acquisition model analysis

???3.4.8 下游客户评价 Downstream customer evaluation

???3.4.9 核心竞争力分析Core competitiveness analysis

???3.4.10 未来战略规划 Future strategic planning

4.?研究总结与展望 Research Summary and Prospects"