深度学习在网络流量分析与威胁情报处理中的应用  

Application of Deep Learning in Network Traffic Analysis and Threat Intelligence Processing

作　　者：郝鹏 HAO Peng(Xingtai Renze District Power Supply Branch of State Grid Hebei Electric Power Co.,Ltd.,Xingtai 055150,China)

机构地区：[1]国网河北省电力有限公司邢台市任泽区供电分公司,河北邢台055150

出　　处：《通信电源技术》2023年第22期166-168,共3页Telecom Power Technology

摘　　要：随着网络攻击的日益增多和复杂化,网络流量分析和威胁情报处理成为保护网络安全的重要任务。深度学习作为一种强大的机器学习方法,具有在复杂数据中提取特征和进行高级模式识别的能力,广泛应用于网络流量分析和威胁情报处理。首先介绍深度学习在网络流量分析中的应用,其次探讨深度学习在威胁情报处理中的应用,最后讨论深度学习在网络流量分析与威胁情报处理中面临的挑战,并提出可能的解决方案。With the increasing and complex network attacks,network traffic analysis and threat intelligence processing has become an important task to protect network security.As a powerful machine learning method,deep learning has the ability to extract features and advanced pattern recognition from complex data,and is widely used in the field of network traffic analysis and threat intelligence processing.This paper first introduces the application of deep learning in network traffic analysis,then discusses the application of deep learning in threat intelligence processing,and finally discusses the challenges faced by deep learning in network traffic analysis and threat intelligence processing,as well as the possible solutions.

关 键 词：深度学习 网络流量分析 威胁情报处理 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]