Shulou(Shulou.com)06/01 Report--

Time flies, the 9th DTCC China Database Technology Conference is about to begin, are you impatient at this time? I know that at this time, I must be looking forward to the 9th DTCC event, but I am sorry that the date of the conference can never be advanced, but the editor can give you some pre-dinner snacks. When the conference is about to open, the editor has a brief exchange with the guests of this year's DTCC conference, Mr. qu Yuehui, a Hadoop technical expert from Meizu.

Qu Yuehui, Hadoop Technical expert of Meizu

In big data's technology field, qu Yuehui can be called a "veteran". He has been engaged in big data-related R & D since 2011. After joining Meizu in 2014, he was mainly responsible for the company-level big data platform architecture planning, design and infrastructure construction, Hadoop eco-technology component selection and R & D, operation and maintenance technical support and other related work. The theme of this year's DTCC speech is "Meizu big data Security practice", mainly from the level of data security to let everyone understand different Meizu, then today we will discuss those things about data security with qu Yuehui.

Data security trend forecast

Doing data without talking about security may not be much different from playing hooligans. Through relevant reports, it is not difficult to find that large-scale data security incidents have occurred frequently in recent years, and data security issues have once aroused the great attention of enterprises and individuals. Qu Yuehui believes that with the continuous catalysis of data security leakage incidents, government laws and regulations will be more sound, users will pay more attention, and data security will also become a core competitiveness. Secondly, the development of data security technology, such as block chain technology (decentralization), data security fusion of artificial intelligence (security protection to achieve static to dynamic, from deterministic behavior to intelligent prediction) will gradually form a system. Qu Yuehui believes that data security may face the following risks:

Individual ● users lack data security awareness and lack of awareness of the risks caused by private data disclosure.

● lacks a unified security standard, does not know how to implement data security control, or there is controversy.

The defense capability of ● platform and security technology is insufficient, and data security lags behind the development of business.

● failed to implement security grading mechanisms, such as data service scenarios, data types, and so on.

Sensitive data such as ● user privacy have not been desensitized.

● data transmission is not encrypted to prevent hackers from stealing.

● fails to audit user behavior, such as the lack of reliable verification channels after data leaks.

The fraudulent behavior of ● data, such as falsified data leading to wrong conclusions.

The data security risk challenges of ● cloud services, such as the high concentration of data and computing, are vulnerable to hackers.

From this point of view, the data faces this huge security risk. Friends who know Meizu all know that Meizu has a large user base, so there are naturally many users' data, especially as people rely on mobile terminals, and the mobile end often stores a large amount of users' personal data. how does Meizu ensure the security of user data?

Meizu's concept of data Security

Qu Yuehui said that Meizu itself feels the same way on the issue of data security, and sometimes a brand new mobile phone product has been fully exposed on the Internet before it is officially released. He mentioned that Meizu attached great importance to the construction of data security from the very beginning, and emphasized the protection of data in the process of data collection and data processing in the process of establishing the data team. According to the introduction, Meizu took data security as the core assessment item in 2017. After a whole year of efforts, Meizu has established a comprehensive security system from norms, clusters, platforms, businesses and so on.

Some friends may say that with the landing application of cloud computing technology, the cloud on the data brings more convenience to users, but it also brings more risks to the data invisibly. Qu Yuehui believes that cloud services provide storage and access to cloud data, which are favored by consumers because of their low cost and convenience, but also because of the high concentration of data and computing in cloud services, the interconnection of networks and other factors. There is no doubt that the security challenges are also the biggest. There are only a few who really do a good job in the security of cloud services and cloud data (which can be trusted by consumers).

For Meizu, at present, it is mainly private cloud, while the cloud services provided in some business scenarios are more likely to help users choose a third-party reliable cloud service company for cooperation from a professional point of view. at the same time in the cloud data storage access interface layer to do adequate boundary protection (such as user authentication, SMS verification, etc.) and data migration interface service support. Of course, due to the rise of big data and artificial intelligence technology, Meizu is also actively exploring how to use the application protection capabilities of big data and AI technology in the security field to develop services and products that compete for the commanding heights of data security competition.

In addition to cloud computing, artificial intelligence technology has gradually matured in recent years. In qu Yuehui's words, the development of science and technology is a "double-edged sword", and so is AI technology. In the field of security, it was previously exposed on the Internet that there are major security loopholes in Google's machine learning platform TensorFlow, which brings enlightenment: if developers want to develop deep learning from 0 to 1 to carry out security attacks, it is extremely laborious or even impossible, but for some mainstream machine learning platforms, such as TensorFlow, because of its high exposure and dissemination, it is very easy for developers to use, thus bringing hidden dangers to data security.

Of course, it is undeniable that the application of AI technology also brings convenience to the security work: when the data security protection technology is integrated with artificial intelligence, it can be realized from static to dynamic, from known possible deterministic behavior to intelligent prediction, thus injecting security enhancement factors into the data security protection system. For example, the current monitoring system module in the big data platform security system of Meizu has earlier introduced the project of Apache Eagle as part of the functions of the platform. Apache Eagle has a particularly noteworthy functional feature, that is, it integrates machine learning to create portraits of users to achieve intelligent real-time protection of big data's security.

DTCC China Database Technology Conference is already in its ninth year, and the theme of this year's conference is "taking the lead in numbers? win the Future". Qu Yuehui said that in 2014, Alibaba founder Jack Ma put forward the view that "mankind is moving from the IT era to the DT era." the current popularity of big data, cloud computing and artificial intelligence also confirms this view, and we are in the DT era. A variety of private cloud, public cloud, AI voice, face recognition and other technologies undoubtedly provide great convenience to our lives, and continue to promote industry change.

In this situation, whoever has the ability to acquire big data will win the first opportunity. At the same time, big data and artificial intelligence complement each other. Big data provides the source power for artificial intelligence. Artificial intelligence gives full play to big data's value, helps enterprises carry out industrial upgrading, provides fine services for the general public, and wins development and the future.

The 9th China Database Technology Conference (DTCC2018) will be officially held from May 10 to 12, 2018. This year's Congress takes the lead in numbers. With the theme of "win the Future", two main venues and 22 special technical venues are set up to invite more than 100 technical experts from the Internet, finance, education and other industries at home and abroad to discuss forward-looking hot topics and technologies in the fields of Oracle, MySQL, NoSQL, big data, machine learning, blockchain and data visualization. For more information about the conference, please visit the official website of DTCC 2018: http://dtcc.it168.com/.

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