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
Link To Document :
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