Big Data Application and Non-traditional Security Threat Governance

Big Data Application and Non-traditional Security Threat Governance

Big data is a massive data state and storage technology, which can effectively integrate information resources in many fields. Through its analysis, processing and application, it can produce products and services with great value. In fact, the application of big data analysis in preventing non-traditional security threats has long been exemplified in European and American countries. For example, the National Oceanic and Atmospheric Administration of the United States uses big data methods to assist climate, ecosystem and weather research; The tool "Google Influenza Trend" uses the summarized Google search data to estimate the influenza epidemic and effectively track and respond to the disease outbreak.

The main reasons why big data contributes to the governance of non-traditional security threats are as follows: First, big data shows the correlation between things, that is, the relationship between the research object and other things, which coincides with the concept of collaborative response to non-traditional security threats and the practice of linkage governance. Second, big data makes it possible to obtain large enough sample data or even all data, which provides sufficient conditions for decision makers to grasp more comprehensive information or more powerful evidence and enhance the scientific decision-making in response to non-traditional security threats. Third, big data has a significant forecasting function, which can predict possible future events according to existing data information and make plans in advance. Fourth, the excellent data collection ability and network collection method of Big Data can realize massive data links across regions and platforms, and can present data in a visual form, which greatly facilitates the handling of some dynamic and complex problems. From the above analysis, we can see that the characteristics of big data inherently meet the logical needs of human beings to control non-traditional security threats. Therefore, it is reasonable to think that the application of big data has great potential for managing complex non-traditional security threats. In view of the fact that big data has become an increasingly important resource in the information society, it is imperative to build and apply big data and improve the government's ability to deal with non-traditional security threats.

Recognize the inherent characteristics and practical application dilemma of big data, and grasp the governance law of non-traditional security threats of big data services.

Although big data is called "an important factor of production that permeates every industry and business function field today" or "an important means and way to promote the government's scientific and democratic decision-making and improve the government's governance ability", it is difficult to fully apply the advantages of big data to the governance of non-traditional security threats without a deep understanding of the inherent characteristics and practical application difficulties of big data and taking corresponding countermeasures.

The inherent characteristics of big data are mainly manifested in the following aspects: First, the effectiveness of big data depends on the authenticity of the data. Big data processing, the first thing is to obtain and record data. Big data is not enough if the data obtained and recorded are untrue or flawed. Second, big data is mostly presented in an unstructured way, with outstanding heterozygosity, and it cannot be used without technical operation and processing. Third, big data is considered to be "longer than analyzing correlation rather than causality". As the saying goes, big data is looking for the correlation between things, not telling people the exact reason why something happened, but reminding people of what is happening. But based on this, we can't come to the conclusion that big data is a negation of the theoretical significance of causality. The significance of understanding the inherent characteristics of big data lies in profoundly grasping the laws of big data in order to better apply big data to serve real life.

In addition, using big data to deal with non-traditional security threats requires attention to the practical application dilemma of big data. First, there is a contradiction between data openness, enjoyment and security in big data applications. At present, many fields urgently need open sharing of data and information among countries, but how to ensure data security in open sharing is a realistic dilemma that is difficult to balance in the application of big data. There is a certain conflict between the principle of data sovereignty and the construction of global interconnection. Second, there are many isolated islands of big data storage, the phenomenon of idleness is prominent, and the level of data application is low. At present, both enterprises and governments have a large number of basic data storage, but they do not share each other's data, nor do they pay attention to data analysis and application. In particular, there is a widespread "data island" in domestic government departments, which leads to data locking, idleness, extensive processing and poor usability. Third, big data analysis is weak and compound talents are lacking. At present, the application of big data in China is still in the exploratory stage, and there is a serious shortage of innovative talents who can directly engage in the analysis and application of big data, which has largely become a bottleneck restricting the application of big data in government governance affairs.

Applying big data to improve the government's ability to control non-traditional security threats

The era of big data has arrived, and it is imperative to apply big data to improve the government's ability to control non-traditional security threats.

First of all, it is urgent to establish a unified data information platform. This is not only because the value of data itself lies in being used, and openness and * * * sharing are the requirements of big data, but also building a unified and open data information platform is a necessary way to break the dilemma of "data island" and "information blockade", promote international cooperation and mobilize people to participate in preventing non-traditional security threats. It is also the need for the government to provide public services to the society to establish a unified and shared data information platform and accelerate the opening of public data resources to the society.

Second, establish big data thinking and actively explore new ways and methods to control non-traditional security threats by applying big data services. In recent years, European and American countries have had successful experience in applying big data to control non-traditional security threats, such as traffic congestion, epidemic prevention and environmental pollution. There are also many explorations and attempts in social public opinion risk assessment and air quality detection in China, but there is still a broad space for applying big data to control non-traditional security threats, which needs to be explored and developed. For example, how to introduce more big data risk control management tools to ensure that consumer finance business becomes a stable long-term credit market; How to use biosensor, ecological remote sensing, big data, cloud computing and other technologies to improve the quality of land planning and avoid land waste and loss. At present, non-traditional security threats are intensifying and intertwined with traditional security threats. Policymakers must rely on big data analysis and application to enhance their governance capabilities in order to deal with various security threats. In other words, the advantages of big data can make a difference in preventing various security threats. To this end, it is of great value to explore new ways and methods of applying big data to deal with non-traditional security threats, and to improve the innovative ability in preventing financial risks, maintaining energy security, food security and information security. In addition, to establish big data thinking and promote big data application, it is necessary to strengthen data source management, and we must attach great importance to the technical analysis of big data and the development of professional and technical human resources.

Third, efforts should be made to promote data openness and * * * sharing, and the information security boundary should be defined by the system. With the rapid development of Internet technology, the incidents of stealing and reselling classified information by using security loopholes or back doors of information networks frequently occur, and there are a large number of virus infections, network attacks and malicious disclosure of personal privacy and business secrets, which just proves that information security itself is one of the non-traditional security threats. Therefore, it is urgent to define the boundaries of data security through institutional arrangements, and formulate regulations, implementation rules and data protection laws for government information at the national level.