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Anomaly-based model for detecting HTTP-tunnel traffic using network behavior analysis 被引量:2

Anomaly-based model for detecting HTTP-tunnel traffic using network behavior analysis
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摘要 Increasing time-spent online has amplified users' exposure to the threat of information leakage.Although existing security systems(such as firewalls and intrusion detection systems) can satisfy most of the security requirements of network administrators,they are not suitable for detecting the activities of applying the HTTP-tunnel technique to steal users' private information.This paper focuses on a network behavior-based method to address the limitations of the existing protection systems.At first,it analyzes the normal network behavior pattern over HTTP traffic and select four features.Then,it presents an anomaly-based detection model that applies a hierarchical clustering technique and a scoring mechanism.It also uses real-world data to validate that the selected features are useful.The experiments have demonstrated that the model could achieve over 93%hit-rate with only about 3%falsepositive rate.It is regarded confidently that the approach is a complementary technique to the existing security systems. Increasing time-spent online has amplified users' exposure to tile tilreat oI miormanon leakage. Although existing security systems (such as firewalls and intrusion detection systems) can satisfy most of the security requirements of network administrators, they are not suitable for detecting the activities of applying the HTTP-tunnel technique to steal users' private information. This paper focuses on a network behavior-based method to address the limitations of the existing protection systems. At first, it analyzes the normal network behavior pattern over HTI'P traffic and select four features. Then, it pres- ents an anomaly-based detection model that applies a hierarchical clustering technique and a scoring mechanism. It also uses real-world data to validate that the selected features are useful. The experiments have demonstrated that the model could achieve over 93% hit-rate with only about 3% false- positive rate. It is regarded confidently that the approach is a complementary technique to the existing security systems.
出处 《High Technology Letters》 EI CAS 2014年第1期63-69,共7页 高技术通讯(英文版)
基金 Supported by the National Natural Science Foundation of China(No.61070185,61003261) the Knowledge Innovation Program of the Chinese Academy of Sciences(No.XDA06030200)
关键词 网络行为分析 HTTP隧道 入侵检测系统 检测模型 交通网络 异常 安全系统 隧道技术 network security, anomaly detection model, hierarchical clustering, HTFP-tunnel
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