Construction of an Enterprise Information Network Security Management System Based on Artificial Intelligence

In recent years, the rapid development of the Internet and information technology has exacerbated the complexity and threat of the network security environment, and enterprises are facing unprecedented challenges. To address this dilemma, this article proposes an enterprise information network security management system that integrates artificial intelligence technology. The system significantly improves the effectiveness of enterprise network security protection through intelligent threat detection, deep behavior analysis, and automated response strategies. The empirical results show that the threat detection accuracy of the system is over 95%, effectively curbing potential security risks. Its successful application signifies that enterprises can more intelligently and efficiently ensure business continuity when facing complex network threats.

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Publication Details

Journal
Procedia Computer Science
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procs.2025.04.018
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Construction of an Enterprise Information Network Security Management System Based on Artificial Intelligence

Ming Li
Procedia Computer Science
Network Security and Intrusion Detection
article

Construction of an Enterprise Information Network Security Management System Based on Artificial Intelligence

Ming Li
article en

Abstract

In recent years, the rapid development of the Internet and information technology has exacerbated the complexity and threat of the network security environment, and enterprises are facing unprecedented challenges. To address this dilemma, this article proposes an enterprise information network security management system that integrates artificial intelligence technology. The system significantly improves the effectiveness of enterprise network security protection through intelligent threat detection, deep behavior analysis, and automated response strategies. The empirical results show that the threat detection accuracy of the system is over 95%, effectively curbing potential security risks. Its successful application signifies that enterprises can more intelligently and efficiently ensure business continuity when facing complex network threats.

Procedia Computer ScienceVol. 259
Datang Telecom Group (China) (CN)
Openalex Percentile: Top 90%
Network Security and Intrusion Detection
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