The big data security problem becomes a consensus industry trust system needs to be established
Deng Maicun also called on all parties in the industry to explore big data theory, methods and key application technologies, and continuously improve data analysis and processing capabilities, knowledge discovery capabilities and decision-making capabilities to form a safe and reliable big data system.
Big data security challenges have almost reached consensus in the industry. As Professor Pan Jianwei, an academician of the Chinese Academy of Sciences and executive vice president of the University of Science and Technology of China, said: “When collecting data for a wide variety of resources, the first challenge is the security of the Internet. We hope that the data can be safely Collect.†In his view, the new quantum revolution or quantum communication leap is also to make big data analysis safer and more efficient.
Yu Xiaohui, chief engineer of China Information and Communication Research Institute, also said in his speech that how to solve the problem of security and trust becomes a top priority when releasing the potential of big data.
Security and trust issues in our country the situation is grim <br> <br>, data transaction industry has just started. In April 2015, the first data transaction platform in China, the Guiyang Big Data Exchange, was officially launched. As of October 2016, China has built and operated more than 10 big data exchanges (or trading platforms).
Yu Xiaohui revealed that by the middle of 2017, the number of big data exchanges (or trading platforms) will reach 15-20. It can be said that the platform construction is in the blowout period, and the liquidity of the platform is steadily improving. It is worth noting that with the strengthening of circulation links, in terms of personal data collection, massive data collection is more difficult, and the transparency in the collection process is relatively low.
Yu Xiaohui pointed out that in the process of data analysis, through the deep mining and analysis of data, user images can be formed, which will pose a threat to personal privacy, and in the circulation link, the control of data transfer is poor due to the involvement of multiple parties. The risk of disclosure is increasing.
He also stressed that in the area of ​​data transactions, there are some problems due to the lack of uniform data transaction rules. First, the ownership of data is not clear, and the subject matter of the transaction is also very controversial. Second, the evaluation of data assets is difficult due to the inconsistent pricing model of data; the third is that data security issues are more prominent, and how to ensure that data is not being used in the transaction process. Leaking, stealing, tampering, and copying are important issues that need to be resolved. Fourth, data transaction regulatory agencies are not clear.
Confidence-building system to overcome three major problems <br> <br> as Yu Xiaohui said, the current data is at blowout of the trading platform, but the data resource trading mechanism, pricing mechanisms and initiatives standardize transactions are not yet clear. Yu Xiaohui called for the standard big data circulation trust system to be established urgently, and the establishment of a standardized big data circulation trust system needs to solve three major problems.
First, the issue of data ownership needs to be accurately defined. Traditionally, ownership of data should belong to the original provider of the data. However, based on the original user data, after removing the personal identity attribute, how to divide the data subject and the data controller's property rights boundary is urgently recognized by the industry.
Second, the issue of data privacy protection needs to be vigorously regulated. At present, the marketing behavior based on big data to analyze the user's behavior characteristics and to derive user preferences has been widely carried out. However, the issue of personal privacy disclosure related to this has also been widely discussed. The protection of citizens' personal information is incompatible with the acquisition and use of data. The laws and regulations in this area need to be improved.
Third, there is a lack of consensus on standards in all aspects of data circulation. The more standardized a product is, the easier it is to trade it. However, due to the nature of the data itself, its cleaning, analysis, storage, pricing and other issues have certain specialities. Data buyers are not aware of the effects of data usage in advance, and therefore cannot judge the reasonableness of data prices, resulting in insufficient data buyer demand.
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