Combating self-learning worms by using predators

摘要：

Internet worms increasingly threaten the Internet hosts and services. More terribly, good point set scanning-based selflearning 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.

关键词： good point set scanning predator interaction model self-learning worms

作者: Fangwei Wang Yunkai Zhang Honggang Guo Changguang Wang

作者单位: Network Center, Hebei Normal University, Shijiazhuang, China College of Physics Science, Hebei Normal University, Shijiazhuang, China

会议类型: 国际会议

会议名称: 2010 IEEE International Conference Conferenhce on Wireless Communications,Networking and Information Security(2010 IEEE 无线通信、网络技术与信息安全国际会议 WCNIS)

会议地点: 北京

会议语种:英文

页码: 1-5

在线出版日期: 2010-06-25（万方平台首次上网日期，不代表论文的发表时间）