RESEARCH ON THE APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGY IN NETWORK INFORMATION SECURITY
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Abstract
Background and Purpose: With the rapid advancement of information technology, cyber threats have become increasingly complex, rendering traditional network security mechanisms insufficient. Artificial intelligence (AI), with its strong computational power and pattern recognition capabilities, has emerged as a promising approach for enhancing network information security. This study aims to examine the core applications of AI in network information security and to explore strategies for improving its effectiveness and adaptability in practical defense scenarios.
Methods: This paper reviews and analyzes existing AI-based security technologies applied to threat detection, attack defense, data security, and privacy protection. Key challenges in real-world applications are identified, and optimization strategies are proposed, including algorithm enhancement, intelligent counterattack mechanisms, improvements in computational efficiency, and the implementation of automated security policies.
Results: The analysis indicates that AI-based approaches can significantly improve the accuracy and timeliness of threat detection and response. Optimized algorithms and automated defense strategies enhance system adaptability, reduce false alarms, and strengthen overall security performance against emerging and sophisticated cyberattacks.
Conclusion: AI has substantial potential to transform network information security. Through targeted optimization of algorithms, defense strategies, and system efficiency, AI-driven security systems can achieve higher resilience and adaptability, providing effective technical support for modern network security challenges.