Dissertation > Excellent graduate degree dissertation topics show

Research and Implementation of DDoS Detection System Based on Self-Similar Traffic Model

Author: JingJie
Tutor: RenXinHua
School: Taiyuan University of Technology
Course: Applied Computer Technology
Keywords: Distributed denial of service attacks Hurst parameter Real-time detection The variance - Time Figure
CLC: TP393.08
Type: Master's thesis
Year: 2008
Downloads: 125
Quote: 4
Read: Download Dissertation

Abstract


With the rapidly growing popularity of Web-based applications , many of the key services provided through the network so how can we ensure network security and availability to become one of the most important issues in network security research . In recent years , serious security incursions have occurred , many critical network applications are under threat , the government network systems , the banking network system , an important network servers . Distributed Denial of Service (Distributed Denial of Service, or DDoS) attack to run out of network resources , so that the service is unavailable , one of the most difficult to solve network security problems . Although a lot of research around this issue , but the work to prevent DDoS attacks did not achieve substantial major breakthrough . This paper studies how accurate and timely detection of DDoS attacks . In order to be able to timely and accurate detection of DDoS attacks occur in accordance with normal network traffic model should be consistent with the self-similar model , the traffic generated by the DDoS attacks will change the thinking of the self-similar characteristics of the normal network traffic to detect DDoS attacks occur . Characterization of self-similar process Hurst parameters calculated a variety , can be roughly divided into the graphical method and two types of non-graphical method , but the sample size of these two methods , the calculation process is slower on storage capacity and computing power requirements are high , suitable for use in offline analysis , real-time online can not meet the requirements of the Hurst parameter values ??in the process of self-similar . This article studies the DDoS attack detection system based on self-similar model , solving the problems of the Hurst parameter values ??exist for the process of self-similar tradition , the difference between a time Figure ( VarianceTimePlots , in the other , referred to as VTP ) on the basis of the analysis , improved VTP real-time online the Hurst parameter method ( On -Time VTP referred to as OTVTP ) performance , draw the conclusion efficiency ; and use the technology , according to the hardware and software environment of the laboratory , and ultimately achieve based on self-similarity DDoS attack detection system , which greatly improved the timeliness and accuracy of detection .

Related Dissertations

  1. Research on Streaming Media Detection Methods Against DoS\DDoS Attack Based on Analysis of Self-similarity,TP393.08
  2. Based on flow characteristics of Campus Network Performance Analysis and Research,TP393.18
  3. Research and Implementation of Real-time Detection of Aggregate Gradation System,U415.5
  4. Flow-based self-similarity in IPv6 DDoS detection method,TP393.08
  5. The Research of Network Traffic Detection and Prediction Analysis Technology,TP393.06
  6. Network anomaly detection model design,TP393.06
  7. Detection of Distributed Denial of Service Based on Fractal Characteristic of Network Traffic,TP393.08
  8. Self-similar model based on network performance optimization,TP393.06
  9. Research on Self-similarity of Network Traffic,TP393.07
  10. Research on the Self-similarity of Network Traffic,TP393.06
  11. The Research of DDoS Attack Detection Technology,TP393.08
  12. Application of Wavelet Transform in Network Traffic,TP393.07
  13. Based on self-similarity of network traffic sampling method research and application,TP393.06
  14. Research on Self-Similar Models of Network Traffic and Parameter Estimations,TN915.01
  15. Self-similarity of network traffic analysis and its application,TP393.02
  16. The IP MAN flow modeling studies,TP393.02
  17. Self-similarity of network traffic analysis and research,TP393.06
  18. Analysis of Network Traffic Based on Campus Network Data,TP393.18
  19. Analysis and application of network traffic based on wavelet transform,TP393.06
  20. The OBS network edge aggregation and shaping algorithm,TN929.1
  21. Network self-similar traffic generated by research,TN915

CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Computer network > General issues > Computer Network Security
© 2012 www.DissertationTopic.Net  Mobile