The Dilemma Of Digital Economy
The most critical and cardinal element of the digital economy is data. Data is the “oil” of digital economy. Hence, utilizing the “data oil” safely and efficiently is the focal point of global economic digital transformation. On the one hand, the digital economy has entered a high-speed development age. The global digital economy has reached 36.2% of global GDP. It is necessary to open up the “data island” among enterprises and establish an open and shared digital resource environment. On the other hand, the public is paying more and more attention to personal privacy and data security, and regulators have introduced a series of regulations to ensure information security. For example, car companies buy parts back and assemble them into cars, the ownership belongs to the car companies, while parts manufacturers also make it clear that once the parts are sold to factories, the factories have ownership. But the data level is more sensitive. Personal data include the face, voice, name, height and other sensitive personal privacy specifics. How to define the ownership of the data between these parties? At present, there are no clear legal provisions, nor the industry has clear answers. In foreign practice, the EU has made very strict data protection regulations, but the entire EU data information technology industry lags behind China and the United States.
Because data protection is too strict, data from different sources do not interact, data is not open and can not interact to generate value and to improve the efficiency of the economy as a whole. The EU is not a good example, because it does not balance the relationship between data privacy protection and the development of the data industry.
Privacy protection and data security need multi-party promotion
Facing the dilemma of data security and sharing, the “available and invisible” secure multi-party computing provides us with an innovative solution.
Secure multi-party computing is a calculation process performed by multiple participants. Multi-party computing technology includes inadvertent transmission, secret sharing and confusing circuit. Multi-party computing has the advantage of high confidentiality and maneuverability, and each party has absolute control over the data it owns. Secure multi-party computing can be applied to networks where participants are not trusted. Participants can know the agreed results of collaborative computation, but they can’t get or deduce the original contents of the data. The flow of data and the collaborative analysis are of great value in all industries, and have brought about a lot of application demands. There are two main scenarios in the market:
1) Data security query
In the big data age, the data that the enterprise holds itself often cannot satisfy the demand of business analysis, many enterprises will purchase the external data to expand the data source. When an enterprise uses an external database to query, it faces the risk of divulging the query condition information. MPC technology helps enterprises to set up a secure query to obtain more external data under the condition of ensuring their own data security, thereby deepening the digital transformation and making better use of big data technology to optimize business.
2) Data joint analysis
Joint analysis often faces two headwinds. On one hand, it is illegal to trade personal privacy information. On the other hand, data sharing makes data-holding companies lose their competitive edge. MPC technology, through inadvertently querying, makes the data not public, the query object not exposed, and the results can be correctly given feedback for, which has an important application in the financial risk control business.
Lumino: new ideas for secure multi-party computing
Lumino is a large-scale activity that uses secure multi-party computing protocols to generate zero knowledge proof system public reference string (CRS) in a de-trust manner, and it is a prerequisite and an important step for deploying and using privacy-related applications in a decentralized ecosystem. The activity now focuses on the PLONK algorithm. As a practical and efficient zk-SNARK algorithm, PLONK is often used in blockchain projects and communities, which is characterized by only one-time initialization process, i. e. running once, it can be used to support a variety of underlying circuit logic and multi-class application deployment.
Lumino’s vision, from the start, was to link the world’s cryptographic geeks to become co-creators and witnesses of privacy computing infrastructure, not just an event but a ritual. We changed the method of centralizing system parameters into a distributed one. For a truly community-based and open-source blockchain ecosystem, each of which is the most critical link, and each participant who joins makes the bottom one safer, which would be a ceremonial collective wisdom.
Lumino is the cornerstone of subsequent de-centering privacy protection applications based on zero-knowledge proof, and the subsequent de-centralization applications will be safer only if the activity is safely completed.
Andrew Park attined his degree in literature from Oxford University. He published his 7 books in career. He has more than 2 years experience in publication.Now he works news writer on People Babble.
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