• DocumentCode
    3438016
  • Title

    Combating self-learning worms by using predators

  • Author

    Wang, Fangwei ; Zhang, Yunkai ; Guo, Honggang ; Changguang Wang

  • Author_Institution
    Network Center, Hebei Normal Univ., Shijiazhuang, China
  • fYear
    2010
  • fDate
    25-27 June 2010
  • Firstpage
    607
  • Lastpage
    611
  • Abstract
    Internet worms increasingly threaten the Internet hosts and services. More terribly, good point set scanning-based self-learning worms can reach a stupendous propagation speed in virtue of the non-uniform vulnerable-host distribution. In order to combat self-learning worms, this paper proposes an interaction model. Using the interaction model, we obtain the basic reproduction number. The impact of different parameters of predators is studied. Simulation results show that the performance of our proposed models is effective in combating such worms, in terms of decreasing the the number of hosts infected by the prey and reducing the prey propagation speed.
  • Keywords
    Availability; Mathematical model; Operating systems; Stability; Uniform resource locators; Web and internet services; Web server; good point set scanning; interaction model; predator; self-learning worms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications, Networking and Information Security (WCNIS), 2010 IEEE International Conference on
  • Conference_Location
    Beijing, China
  • Print_ISBN
    978-1-4244-5850-9
  • Type

    conf

  • DOI
    10.1109/WCINS.2010.5541851
  • Filename
    5541851