Application of Big Data and Artificial Intelligence in Public Network Information Security Management

With the rapid development of network technology and the diversification of network attack methods, traditional network security protection methods have been difficult to cope with the emerging complex threats. The combination of big data and artificial intelligence technology in public network information security management can not only process and analyze a huge amount of network data, but also provide the ability to automatically identify and predict potential threats. This paper focuses on the application of big data and Artificial Intelligence (AI) technology in threat intelligence collection, network traffic analysis, and network security automation. Finally, two sets of simulation results are as follows: In the public network information system, the system intrusion detection accuracy rate of the improved algorithm is improved by 7.5
^%
on average compared with the traditional method, and the response time of network traffic monitoring is shortened by 2.7s on average. The improved algorithm model proposed in this paper can effectively help the government and enterprises to build a more secure network environment and protect the data security of individuals and organizations.