摘要
文章针对大规模通信网络中异构设备、突发流量以及隐蔽攻击等安全威胁,提出一种涉密信息安全动态预警系统.该系统包括信息采集与识别、风险评估与预警、应急响应模块,融合大数据、机器学习、知识图谱等技术,实现对网络安全态势的实时监测、智能分析以及快速响应.实验结果表明,所提出的系统具有较高的未知威胁发现率、较低的未知威胁误报率以及极短的响应时间,在攻防对抗中表现出优异的防御效能.
Abstract
The article proposes a dynamic warning system for classified information security,targeting security threats such as heterogeneous devices,sudden traffic,and covert attacks in large-scale communication networks.The system includes information collection and recognition,risk assessment and warning,emergency response modules,integrating technologies such as big data,machine learning,and knowledge graphs to achieve real-time monitoring,intelligent analysis,and rapid response to network security situations.The experimental results show that the proposed system has a high unknown threat discovery rate,a low unknown threat false alarm rate,and an extremely short response time,demonstrating excellent defense effectiveness in offensive and defensive confrontations.
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