基于深度学习的网络异常行为检测与分析技术研究  

Detection and Analysis of Network Abnormal Behavior Based on Deep Learning

作　　者：杨迪 YANG Di(Rizhao People̓s Hospital,Rizhao,Shandong 276800,China)

机构地区：[1]日照市人民医院,山东日照276800

出　　处：《移动信息》2024年第9期147-149,共3页Mobile Information

摘　　要：随着网络技术的快速发展,网络异常行为检测与分析技术在网络安全领域的应用变得尤为重要.文中基于深度学习技术,回顾了深度学习的基础理论,探讨了深度学习模型在网络异常行为检测中的应用原理,并分析了数据预处理、特征提取和深度学习模型等的应用,同时将其与传统机器学习方法进行了比较分析,旨在提高网络安全防护能力,确保网络信息系统的安全性.With the rapid development of network technology,the application of network abnormal behavior detection and analysis technology in the field of cyber security has become particularly important.Based on deep learning technology,this paper reviews the basic theory of deep learning,discusses the application principle of deep learning model in network abnormal behavior detection,and analyzes the application of data preprocessing,feature extraction and deep learning model,and compares it with traditional machine learning methods to improve cyber security protection capabilities and ensure the security of network information systems.

关 键 词：深度学习 网络异常行为检测 数据预处理 特征提取 网络安全 

分 类 号：TN915.08[电子电信—通信与信息系统]