Zhang Jiachen said that the design goals of PTS include reliability, fair and transparent value distribution, low latency within one second, privacy protection, compliance, scalability and data fidelity.
At 21:00 on July 19th, invited by Ding Ruoyu, the rotating group leader of the "Mars Finance Founding Learning Group", and the deputy group Advocate Ting, PTS founder Zhang Jiachen was a guest of the "Mars Finance Founding Learning Group", bringing the theme of "PTS Next-Generation Data Collaboration Agreement and Financial Technology" to share.
Points (PTS) founder Jiachen Zhang
Jiachen Zhang is the initiator of dCamp in the Beijing blockchain community, graduated from Harvard Business School, MBA and Kennedy School of Government with a master's degree in public policy, dedicated to creating a high-security blockchain data collaboration protocol, the first batch of applications in kyC and credit scoring fields, has access to billions of data volumes. In 2014, he began to participate in the blockchain industry while working for Tim Draper in Silicon Valley, and was the COO of the Minibot robot business of Xiaomi's ecological chain enterprise, leading the team to create the world's top artificial intelligence and robot developer community.
In the sharing of the evening, Zhang Jiachen first mentioned that we live in an era of data explosion, everyone will produce 17M/S of data, but only 0.5% of these data have been analyzed, and there will be problems such as data leakage in the era of big data, so blockchain technology has a natural advantage in data collaboration.
She also introduced that it is necessary to develop a set of data collaboration protocols and frameworks based on the pan-blockchain technology stack, which can help blockchain leverage its strengths and avoid weaknesses, and promote the data economy and the Internet of value to become a reality.
Zhang Jiachen pointed out that the PTS protocol includes six functional modules: a high-performance consensus mechanism, a verification mechanism based on zero-knowledge proofs, transaction execution based on mechanism contracts, a distributed file exchange system with encrypted communication, a data verification engine, c-end application support, a high-quality cornerstone dataset, and a data contribution reward mechanism based on mutual entropy (mutual entropy theory).
The following are organized according to group sharing:
The age of data explosion
Jiachen Zhang: Thanks to our investors and chief scientific advisors, Professor Zhang Shousheng and Kevin Ding, for the invitation, and it is a pleasure to meet all the new and old friends in the group.
Today, we all recognize that we live in an era of big data explosion, with IDC analysis reporting that everyone generates 17 megabytes of data every second. However, only 0.5% of these data have been analyzed in any kind. In the era of data explosion, data breaches, data silos, data loss and data accuracy problems still exist, data collaboration can generate a lot of value, but privacy security, incentive mechanisms and effective data organization are important issues that need to be solved, and once such a framework is in place, the potential of AI as a productivity will be further stimulated and used by us.
Blockchain technology has natural advantages for data collaboration in some aspects, especially the recording and confirmation of rights in the history of data generation through timestamps, and the token mechanism makes it possible to reward mechanisms for large-scale data collaboration that is more transparent and real-time. However, at the same time, in addition to the limitations of computing performance, the difficulty of tampering with the blockchain has led to the formation of difficulties in privacy protection, and if there is no good specification and correct deployment, it is easy to generate crises and problems. Therefore, the development of a set of data collaboration protocols and frameworks based on the pan-blockchain technology stack can help the blockchain to build on its strengths and avoid its weaknesses, and promote the data economy and the Internet of value to become a reality.
In June of this year, we joined the NEO Foundation in the EU Parliament for a closed-door workshop on blockchain development with EU officials. During this period, EU parliamentary officials invited the PTS team to demonstrate whether blockchain is compatible with GDPR in the European Parliament. We believe that blockchain and GDPR are not only consistent in policy concept, but also can achieve GDPR compliant blockchain data collaboration architecture from the perspective of actual engineering implementation, and we will launch a GDPR compliant version for users with GDPR compliance needs to choose to use.
PTS protocol is an enterprise-class secure and scalable data collaboration protocol that implements secure, high-speed computing based on distributed data sources based on secure multi-party computing as the framework. Our design goals include reliability, fair and transparent value distribution, low latency within a second, privacy protection, compliance, scalability, and data fidelity.
Focus on design integrity and usability
Zhang Jiachen: In the entire pan-blockchain technology stack, the PTS protocol is the protocol and service layer on the public chain architecture, including the following components.
The PTS protocol gives full play to the advantages of blockchain as a distributed ledger and transaction execution engine, and combines cryptography and data masking methods including zero-knowledge proof, asymmetric encryption, data obfuscation, differential privacy and other cryptographic and data desensitization methods in data security to create a strict and secure multi-party computing framework.
Under this framework, multiple data sources can cooperate collaboratively without exposing the original data without mutual trust, and jointly output a calculation result, such as statistical analysis, personal credit score, high-precision user portraits, background survey results, etc.
In terms of scalability, the PTS protocol supports throughput starting from 10,000 TPS and latency within a second by 1) supporting accelerated accounting in the form of deposit-based deposits and 2) sharding technology in the Secure Dropbox Service.
In order to make this data collaboration protocol fully play a role in the entire blockchain ecosystem, we started from the architectural thinking of cloud agnostic and designed the architecture of chain agnostic so that it can support various public chain infrastructures in the long run. After careful testing and screening, we chose the Ontology Ontology Network as our strategic partner in terms of performance, stability and community popularity. Our testnet was launched in early July and deployed on the testnet of the ontology network.
The PTS protocol includes six functional modules: a high-performance consensus mechanism, a verification mechanism based on zero-knowledge proofs, transaction execution based on mechanism contracts, a distributed file exchange system with encrypted communication, a data verification engine, c-end application support, a high-quality cornerstone dataset, and a data contribution reward mechanism based on mutual entropy (mutual entropy theory).
Throughout the design and implementation of the architecture, we place great emphasis on design integrity and usability. Technologies that improve data security, such as data obfuscation, data anonymity, and differential privacy, are all integrated into the design. In the implementation of sharding, PTS focuses on cross shard communication and encapsulates sharding in the SDK, so that the protocol participants do not need to set up and optimize the work themselves.
Take the actual application scenario as the traction
Jiachen Zhang: When we designed the PTS protocol, we took the actual application scenario as the traction, and the PTS credit network was our first series of applications. At present, we have launched a blockchain-based KYC (Know Your Customer) verification application, which can be initiated by individuals to start the authentication process, we are fortunate to cooperate with the Ministry of Industry and Information Technology Academy, as a verification agency for Chinese mainland, they can verify the identity of more than 1 billion users in China, after the relevant documents stored on the user's device side are authenticated, users can rely on the authentication success information recorded on the blockchain to pass kyC certification by different financial service institutions in one stop. Significant time and personnel cost savings for the organization and a safer process. KYC is also one of the key applications of blockchain identified in the Goldman Sachs Bank report and Yao Qian, former director of the Central Bank's Digital Research Institute.
At the same time, we have also obtained strategic investment from Zhongxin Credit, a leading enterprise in the credit reporting industry and one of the eight shareholders of Baixing Credit, and connected personal credit-related variables covering more than 500 million people to the PTS credit network. At present, the credit history of developing countries is still very lacking, taking China as an example, only 30% of people have credit records that can be used for traditional credit scoring models, so based on machine learning and big data credit scoring application space is vast, can help a large number of users without credit history through mobile Internet and other new data to obtain reasonable risk assessment, with a healthy interest rate level to gradually establish a credit history.
The basis of all this is the need to establish a complete and accurate data pool, open up data silos, and form an efficient data collaboration model covering individuals and institutions. Allowing more ordinary people to access healthy and effective credit pathways is one of the most effective economic and social development paths in empirical research in the field of development economics. In the PTS credit network, financial institutions, non-financial institutions and individuals can participate in the collaboration of credit score data and obtain substantial convenience and returns.
Digital assets are a new type of asset
Zhang Jiachen: In addition to helping blockchain enhance financial technology, we believe that digital assets are a new type of asset, and in this new asset class, it is urgent to introduce risk control and precision marketing technologies. For example, there is no risk control method other than collateral in crypto lending, and in fact, after KYC, many asset holders' credit score related information can be introduced into his digital asset service to form a more efficient interest rate and quota level. Personalized portfolio recommendations can also borrow a large extent from the aggregation of relevant dimensional data in the field of precision marketing.
If we go beyond the fintech field, the concept and architecture of the PTS protocol can also support multiple fields including pharmaceutical research based on personal case information, industry statistics, and so on. We look forward to working with our ecosystem partners to implement them one by one and become key facilities underpinning the data economy."
The founding team of PTS comes from Harvard Business School, Harvard Kennedy School of Government, Carnegie Mellon University Computer Department, Tsinghua, Peking University, Kellogg and other well-known institutions at home and abroad, has been responsible for technical and commercial work in Google, Amazon, Xiaomi, Today's Toutiao, CITIC, Microsoft and other enterprises, core engineers have been as chief architects to design and implement a number of large scalable software systems, and have defined the U.S. content industry Digital Right Management (DRM) The industry standard and the development of the industry's leading search engine, the ecological operation team has created a top AI developer community and several hundred million flowing consumer-level businesses from zero to one. PTS's consultants include Professor Zhang Shousheng of Stanford University, Chief Scientific Advisor, Mr. Jason LU, former Vice President and Chief Risk Management Officer of Ant Financial, and Mr. Zhang Bin, CEO of China Chengxin Credit Information. We are very welcome to communicate with us and ask questions.
PTS benefits from a high-performance consensus mechanism
Ding Ruoyu: Let me ask a question first, there are many projects in the underlying technology of the blockchain, including the public chain, but everyone is looking forward to seeing the landing of the application layer. What is SARAH optimistic about on the killer app of the blockchain?
Jiachen Zhang: I think data collaboration enabled applications are a big category, where financial and medical data is the most valuable and requires good security protection. At present, the more mature large-scale application on the blockchain is the payment protocol, but the imagination space and influence of the data collaboration protocol will be greater. In addition, the economy on the blockchain has formed a new asset class, and the corresponding various services will also be a big opportunity. In addition, regtech is also a good application.
Cai Dong: The PTS protocol includes six functional modules: a high-performance consensus mechanism... Another consensus mechanism on the ontology? Does the ontology's own consensus mechanism seem to be NEO DNA, or is it later referred to as Algorand's called ontorand?
Zhang Jiachen: The consensus mechanism of the ontology itself is vbft. The version deployed on the ontology uses the vbft consensus mechanism. We can also support the dpos consensus mechanism.
Ding Ruoyu: pts has a lot of exploration of scalability in solving the credit modeling problem. Talk about your thoughts on this?
Zhang Jiachen: We benefit from the high-performance consensus mechanism, at the same time, we take the off-chain computing for layer 2 scheduling, and the deal with the post based early confirmation, we do the harding in the SDK layer, so that protocol users can enjoy the performance improvement brought by harding without having to set it up.
Zhang Ting: Has the current KYC verification application cooperated with the government?
Jiachen Zhang: Yes, our KYC application in China works with the government to make the government a validator in a distributed KYC system.
Ding Ruoyu: Blockchain and GDPR are a concern for everyone. I heard that pts were the first to indicate that they were compatible. How did you do it?
Zhang Jiachen: The GDPR is a regulation of data protection and privacy for all EU individuals in EU law, the main goal is to regain citizens' control over personal data, and the core requirements are as follows:
Informed consent for processing
Data protection by design and by default
Pseudonymisation
Right of access
Right to erasure
Records of processing activities
Operationally, the performance is:
At the storage level, personal data must be stored using pseudonyms or complete anonymity, and the highest possible privacy settings are used by default.
At the level of use, the data controller or processor has obtained explicit opt-in consent from the data owner, unless it is completed on a lawful basis as stipulated by the regulations, and the data owner has the right to revoke this permission at any time.
At the record level, the personal data processor must clearly disclose any data collection, declare the legitimate basis and purpose of the data processing, how long the data is retained and whether the data is shared with any third party or a country outside the European Union.
At the level of deletion, the user has the right to request a portable copy of the data collected by the processor in a common format and has the right to delete his data in specific cases.
As a data cooperation agreement, PTS supports the deployment of GDPR compatibility through the following points:
By distributing the storage of each data party to store and maintain the database separately, the PTS network itself does not store any data.
All data processing and call histories are fully documented on-chain, and PTS can provide an API interface for individual users to access data usage information, change usage preferences and permissions, or remove themselves from the data network. User options automatically take effect and are enforced on the network.
Finally, the PTS protocol automatically identifies individual EU users and restricts the processing of GDPR-related notifications and record/recall/processing permissions to the corresponding data parties. Therefore, we plan to provide a GDPR-compliant version of the ptes protocol for use by ecosystem partners in need.