Computer Network Information Security and Protection Strategy Based on Big Data Environment

Computer Network Information Security and Protection Strategy Based on Big Data Environment

Min Jin
DOI: 10.4018/IJITSA.319722
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This paper proposed a study on computer network information security and protection strategy based on a big data environment. The research purpose was to use big data technology to network information security protection technology and seek more efficient network information protection technology. The algorithm proposed in this article was a time-series network detection algorithm based on big data, which could improve the early warning rate of abnormal network information, reduce the early warning time, and improve the detection accuracy and interception rate of virus information. The results of this study could effectively show that big data technology had excellent performance in computer network information security protection, which also led to an advanced reform path for future network information security protection technology.
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In recent years, both life and production have been networked, bringing humankind many conveniences. However, everything has advantages and disadvantages. The growing network information security crisis has had a great security impact on mankind. In the informatization process, addressing computer network information security is a challenge that must be faced. Aiming to address the challenges mentioned, the study focuses on using big data technology to optimize the protection capability of network information security (Chang & Seow, 2019). This research would improve the detection speed and accuracy of abnormal network information and expand the application direction of big data, consequently promoting intelligent protection of network security. At present, the study of network information protection technology in scientific research has been improving and can better address various dangerous network attacks and intrusion operations at this stage. However, with the emergence of big data technology, conventional anomaly network information detection technology is difficult to apply. Therefore, big data technology should be combined with traditional anomaly network information detection technology to develop a more efficient anomaly network information detection and protection technology (Zhu, 2021). However, in academic circles, the current research status of computer network information security and protection under the background of big data remains in the initial stage of development.

Since the rapid advancement of an information-based society, computer network information security has gradually become a popular research area. Several scholars have conducted scientific and comprehensive studies on this topic. Yang (2020) believed that computer network information security protection was the key direction for enterprises. He introduced computer network information security by analyzing and comparing numerous reference materials. Second, he analyzed the risks faced by computer network information security. Then, he noted that the computer network information security management system should be improved to strengthen security awareness and maintain the network security environment. His research summarized the application of protection strategies to maintain computer network information security, which provided a reference for related information security research (Yang, 2020). Deng (2020) pointed out that computer technology was increasingly used in work, life, and study. He analyzed the major problems of computer information systems in security protection. His study referred to network information security protection norms and guidelines and proposed multilevel and multifaceted protection technical measures for information security management systems. In addition, he investigated the design framework of a reliable information security management system, which provided a useful reference value for the design of the information security management system (Deng, 2020). Shi (2017) noted that network information security was dominated by a variety of factors, suggesting operation complexities during assessment. To address this challenge, he studied network information security assessment and used an assessment model and algorithm based on correlation clustering analysis. The relevant influencing factors were comprehensively analyzed, and the network security evaluation index system was developed. In addition, he calculated the category of network information security level by normalizing different evaluation indicators. His research proved the feasibility and operability of the evaluation model (Shi, 2017). Carapico and Farrand (2017) believed that protecting cyberspace had become one priority of cybersecurity policies. He believed that the field of network information protection included network crime, key information infrastructure, and network defense. He pointed out that the important role of the network detection department could be determined using the network supervision framework supplemented by network governance insights. In addition, he also guided the countermeasures of network information security supervision and proposed important decisions for protecting network information security (Carrapico & Farrand, 2017). The abovementioned research topics have also delved into computer network information security from multiple directions, and their findings played a guiding role in the growth of network information security; they also provided hints on the research content of this topic. Despite the increasing importance of computer network information security and big data, there remains a notable research gap in their relationship, indicating the urgent need for further exploration.

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