首页|基于异常流量检测和场景编排的自动化安全运营体系

基于异常流量检测和场景编排的自动化安全运营体系

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传统安全监控系统不仅效率不佳,而且还会产生大量误报.安全人员通过手工的方式处理大量告警信息,很容易忽略真实且有危害的信息.为此,提出了一种基于异常流量检测的SOAR自动化响应运营体系,以提升业务操作效率和安全管理人员的工作效率,实现安全运营的精细化、自动化.同时,对于未知威胁,通过人工智能模型进行全流量分析,形成未知威胁的快速发现、溯源以及快速处置等能力,可以突破传统方法在未知威胁分析方面的技术瓶颈.
Automated Security Operation System Based on Anomaly Traffic Detection and Scenario Orchestration
Traditional security monitoring systems not only have poor efficiency,but also generate a large number of false alarms.Security personnel can easily ignore real and harmful information by manually processing a large amount of alarm information.To this end,a SOAR automated response operation system based on abnormal traffic detection is proposed to improve the efficiency of business operations and the work efficiency of security management personnel,and achieve the refinement and automation of security operations.At the same time,for unknown threats,using artificial intelligence models for full traffic analysis can form the ability to quickly discover,trace,and dispose of unknown threats,which can break through the technical bottleneck of traditional methods in unknown threat analysis.

anomaly traffic analysisCNNsecurity scenario orchestratio

李玮、李铭阳

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中国移动通信集团陕西有限公司,陕西西安 710061

异常流量分析 卷积神经网络 安全场景编排

陕西省重点研发计划项目陕西省自然科学基础研究计划资助项目西安市科技计划项目碑林区科技计划项目

2023-YBGY-2272023-JC-QN-07052022JH-RYFW-0138GX2216

2024

自动化应用
重庆西南信息有限公司

自动化应用

影响因子:0.156
ISSN:1674-778X
年,卷(期):2024.65(8)
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