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
维普
万方数据