信息安全研究2025，Vol.11Issue(1)：66-73,8.DOI:10.12379/j.issn.2096-1057.2025.01.10
基于深度学习的多会话协同攻击加密流量检测技术研究
Encrypted Traffic Detection Technology for Multi-session Coordinated Attack Based on Deep Learning
周成胜 1孟楠 1赵勋 1邱情芳2
作者信息
- 1. 中国信息通信研究院安全研究所 北京 100191
- 2. 北京鉴衡认证中心有限公司 北京 100010
- 折叠
摘要
Abstract
Malicious encrypted traffic detection is currently an important research topic in the field of network security.Attacker used multi-session encrypted traffic to achieve multi-stage coordinated attacks,which is becoming a trend.This paper analyzes the existing problems of current mainstream malicious encrypted traffic detection methods,and proposes an malicious encrypted traffic detection method for multi-session coordinated attack scenarios.Based on the advantages of deep learning methods in the field of image recognition,this method extracts multi-session features and converts them into images,converting encrypted traffic identification problems into image recognition problems,thereby indirectly realizes malicious encrypted traffic detection.The preliminary test results on the experimental data have verified the effectiveness of the method.关键词
深度学习/加密流量/多会话/协同攻击/网络安全Key words
deep learning/encrypted traffic/multi-session/coordinated attack/network security分类
计算机与自动化引用本文复制引用
周成胜,孟楠,赵勋,邱情芳..基于深度学习的多会话协同攻击加密流量检测技术研究[J].信息安全研究,2025,11(1):66-73,8.
