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A Research on High-speed Network Traffic Anomaly Detection Technology
Author: DaiJun
Tutor: WangHong
School: National University of Defense Science and Technology
Course: Computer technology
Keywords: High - speed network traffic Anomaly Detection BFE Information entropy PCA
CLC: TP393.08
Type: Master's thesis
Year: 2008
Downloads: 124
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Abstract
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The operator service bearer class network and industry customers backbone link system is the main representative of the high-speed network . With business systems has expanded each year , part of the enterprise network system more and more reflect the characteristics of the high-speed network , including telecom operators around the bearer network construction support network gradually added to the high - speed network camp . High-speed networks due to its unique characteristics determine its security system , security high-speed internet and also lost customer-oriented basic guarantee to provide qualified service quality can not be thinking of building in accordance with the general security of information systems . The face of the threat of abnormal traffic , high-speed network is needed is a novel idea not only to maintain the robustness of the network system can provide a higher hit rate detection . This article is to explore the new method of high-speed network traffic anomaly detection , in order to improve the ability to detect abnormal network traffic , and network traffic monitoring function using this method . First, network traffic anomaly detection and traffic data collection technology comparison, the existing analysis technique for high-speed network traffic anomaly analysis technique has broad space for development , and comparison of the three collection methods , the flow collection methods selected for this study . Secondly, the suitable for high-speed network traffic anomaly detection system framework model , abnormal online traffic acquisition module , traffic statistics , and pre-processing module , detection module , abnormal after the detection module, alarm and response module , a comprehensive analysis and visualization module function design to achieve high-speed line detection of network traffic . Again , the proposed of BFE traffic anomaly detection method , using a modified Bloom Filter algorithm combined with information entropy distribution characteristics of the network traffic , by the exception to determine flow distribution characteristics abnormal , with less resource overhead , lower computational complexity , reducing the the network anomaly false alarm rate and improve the detection rate . Finally, the PCA - based traffic anomaly detection method , fast and accurate calibration point in time an exception occurs , to help network security emergency response departments to detect network traffic anomalies , abnormal gain time for a quick solution network has better recognition accuracy rate and detection efficiency.
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