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Protecting Personal Data of App Users

In the Internet industry, the competition between enterprises is often the competition of users, and the most important means to control users is the use of data. For Internet enterprises, it can be said that “those who get data get the world.” The accelerated development of the Internet has brought up a number of data-based technology enterprises. Some of them directly made a captive market as winners through monopolizing personal data.

Data security and privacy protection have been a hot topic in recent years. Unfortunately, in some areas, it seems that the improvement of laws cannot keep up with the speed of technological development. The data security risks and the uncoordinated development of the Internet industry have already threatened the development of big data.

In order to use apps , users typically have to transfer some personal information to enterprises. In daily life, many Internet platforms require users to provide nonstructural data such as personal fingerprints, face information, and geographic location information in the process of providing services for users. Many current technology giants use personal data in precision marketing and other strategies. However, if mishandled, these data may threaten the security and privacy of users anytime and anywhere.

Is there any way to solve the problem of protecting personal data in the process of using the app? The answer is yes.

Driven by big data, artificial intelligence is accelerating the intelligent transformation of all industries, and data sharing plays a very important role in this process. The concentration of data in data silos under market monopoly hinders the balanced development of this industry. Once the data is released, the market will return to sound competition, and the data will benefit everyone as public production raw materials. When technology giants no longer monopolize personal data, the real value of data will be released.

To clarify, “releasing data” does not mean to show the data in detail. Rather, it means to return the ownership of data to the data producers, the Internet users themselves. As more and more data security problems appear, some platforms are beginning to use blockchain technology to realize the privatization of data authorization and put the right to use data back into the hands of data owners. With the support of today’s Internet technology, personal data can be stored in mobile phones, smart watches, or the cloud. Users can store data in mobile phones or the cloud, at the same time, they can package and encrypt personal data, and then authorize the data users to carry out encryption calculation, so as to get a certain reward.

In order to make the data flow better, GDF has also introduced data tokenization, which automatically generates unique ERC-20 tokens and the corresponding flow pools for users when they upload a database. The ERC-20 token, which carries data, makes the value of data flow not only between data producers and data users, but also to anyone who wishes to participate. In addition to enhancing the liquidity of data, liquidity mining also provides the function of data value mining, which not only provides better market value reference for data users, but also encourages data providers to provide better and more valuable data.

GoodData’s secure data sharing platform is based on multi-party computation, federated learning, and homomorphic encryption algorithms, among other technologies; it can ensure that the user’s data is available but not visible, so that the data can be safely shared for machine learning. . For example, on GDF’s blockchain platform GoodData, users can share personal data on the premise of privacy protection. Through encryption algorithms, data users can conduct artificial intelligence machine learning on encrypted datasets and calculate accurate results, all without ever viewing the original data. With GoodData, these scattered data can now be combined with various artificial intelligence algorithms, releasing endless value.

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