• DocumentCode
    3772292
  • Title

    Pippy Search: Anomaly Traffic Clustering

  • Author

    Lili Yang;Jie Wang;Mansoor Ahmed Khuhro

  • Author_Institution
    Sch. of Inf. Sci. &
  • fYear
    2015
  • Firstpage
    378
  • Lastpage
    383
  • Abstract
    Terrible network environment is damaging the critical infrastructure and the interests of internet users. In order to ensure the protection and resilience of attack, it is important to better analyze and observe network traffic for discovering anomaly. This paper presents a clustering algorithm by using network-layer and transport-layer statistical feature to classify anomaly traffic. Experiments with public datasets show the proposed algorithm has a significant effectiveness of traffic clustering quality.
  • Keywords
    "Clustering algorithms","Classification algorithms","Payloads","Computer crime","Algorithm design and analysis","Internet","Feature extraction"
  • Publisher
    ieee
  • Conference_Titel
    Smart City/SocialCom/SustainCom (SmartCity), 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/SmartCity.2015.101
  • Filename
    7463755