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