基于人工智能的威胁检测与防护系统

文中针对传统的基于签名匹配的威胁检测系统存在的局限,探讨了人工智能技术在网络安全防护中的应用。通过分析异常检测、恶意软件检测和自动化安全响应3个方面,阐明了机器学习和深度学习模型可以实现对未知威胁的检测和主动防御。研究认为,人工智能驱动的网络安全防护系统代表了技术发展的方向,但还需进一步的数据积累和模型优化,以实现更智能的商业安全产品的开发。

Threat Detection and Protection System Based on Artificial Intelligence

In response to the limitations of traditional signature matching based threat detection systems, this paper explores the application of artificial intelligence technology in network security protection. This paper clarifies that machine learning and deep learning models can achieve detection and active defense against unknown threats by analyzing three aspects: anomaly detection, malware detection, and automated security response. Research suggests that artificial intelligence driven network security protection systems represent the direction of technological development, but further data accumulation and model optimization are needed to achieve more intelligent development of commercial security products.