• DocumentCode
    584350
  • Title

    Detection and Control of Anomaly Network Data Flows

  • Author

    Wenfang, Zhang ; Chi, Xu

  • Author_Institution
    Sch. of Archit. & Urban Planning, Hunan City Univ., Yiyang, China
  • fYear
    2012
  • fDate
    11-13 Aug. 2012
  • Firstpage
    597
  • Lastpage
    600
  • Abstract
    Data flows is a type of dynamic data. After the detection of anomaly data flows, the next problem is how to control these anomaly data flows effectively and prevent network jam. Router queue management is an effective method of controlling anomaly data flows. When network is busy router can prevent it by active droppings. The characters of unresponsive of network congestion control and high-bandwidth were researched deeply to explore the malicious flow effects on the large-scale network. After that, experiments were implemented to present the network congestion collapse resulted from malicious flows and its influences on the network resource allocations.
  • Keywords
    computer network management; computer network reliability; computer network security; data flow analysis; queueing theory; telecommunication congestion control; telecommunication network routing; active dropping; anomaly network data flow control; anomaly network data flow detection; dynamic data; large-scale network; malicious flow effect; network congestion collapse; network congestion control; network jam prevention; network resource allocation; router queue management; Bandwidth; Data mining; Data models; Hidden Markov models; Internet; Intrusion detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science & Service System (CSSS), 2012 International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4673-0721-5
  • Type

    conf

  • DOI
    10.1109/CSSS.2012.154
  • Filename
    6394392