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As the “new oil of the future,” big data is becoming the leading industry of the new economy, the core asset of the country and enterprises, the “new blue ocean” to be pursued, and the national strategy to be developed by all countries. The development of big data and its related technology supports and promotes a new round of technological innovation, making a new generation of information security technology reform and innovation, bringing opportunities and challenges to optimize, and consolidating national information security. In the era of big data, what kind of challenges and impacts will information security face? and is it crucial to explore the response strategies? At present, China has risen to become the world’s largest number of Internet users and the largest number of people using smartphones, but because China’s information security is the initial stage, involving information security, especially national information security laws and regulations are not much, the national social supervision and monitoring mechanisms are not much, the application level of science and technology content is relatively backward, the core technology has a patent technology not much, resulting in the flood of network data nowadays. Therefore, the underground illegal “data industry chain” activities are rampant. Therefore, this paper proposes a security-aware model based on the combination of distributed data analysis technology and data features. The model uses data features to dynamically generate a library of situational anomalies, effectively solving the problem of analyzing and processing rapidly and dynamically generated data streams, increasing the detection rate to more than 98%, effectively reducing the possibility of false detection, and having good results on large-scale datasets. |
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