Research on worm propagation model in IPv6 networks

SU Fei1; LIN Zhao-wen1; MA Yan1; YANG Xiao-ming3

您当前的位置：

首页 >

文章列表页 >

Research on worm propagation model in IPv6 networks

更新时间：2024-10-14

- Research on worm propagation model in IPv6 networks
- Vol. 32, Issue 9, Pages: 51-60(2011)
- 作者机构：
  
  1. 北京邮电大学网络与交换技术国家重点实验室
  2. 北京邮电大学智能通信软件与多媒体北京重点实验室
  3. 工业和信息化部电子第五研究所
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP393.08
- Published：2011
- 稿件说明：
移动端阅览
SU Fei1, LIN Zhao-wen1, MA Yan1, et al. Research on worm propagation model in IPv6 networks[J]. 2011, 32(9): 51-60.
DOI：

SU Fei1, LIN Zhao-wen1, MA Yan1, et al. Research on worm propagation model in IPv6 networks[J]. 2011, 32(9): 51-60. DOI：

摘要

研究了IPv6网络中

蠕虫在子网间和子网内传播的多种扫描策略;讨论了基于P2P的去重复和可控机制;研究了一种能够在IPv6网络中形成大规模传播的新型混合式蠕虫——NHIW。NHIW具有随机扫描蠕虫的特点

同时能够迅速获取子网内的易感染活跃主机IPv6地址

并能解决重复感染的问题。通过研究NHIW不同传播阶段的时延

理论分析其传播率

建立了NHIW的3层传播模型TLWPM。实验表明

NHIW能够在IPv6网络中形成大规模传播。最后

针对NHIW的特点

讨论了相关防御策略。

Abstract

A wide variety of scanning strategies for IPv6 networks when a worm scans across subnets and inside subnets was investigated.A P2P-based mechanism for decreasing the repeated infection and implementing control strategies was discussed

and a new hybrid worm named NHIW

which can form large-scale propagation in IPv6 network

was also constructed.The NHIW can not only scan the worm randomly

but also can quickly obtain IP addresses of susceptible active hosts in the subnet as well.Furthermore

NHIW is able to prevent re-infection of the host.Through analyzing the delay in different stage of NHIW propagation and its propagation rate

a full NHIW propagation model TLWPM was established.Experimental results show that NHIW can form a flooding propagation in the IPv6 network.With respect to the features of NHIW

some relevant defense strategies were discussed finally.

关键词

Keywords

references

Views

835

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Joint estimation of target time delay and Doppler frequency in passive radar system

Approach to worm early warning based on local victim behavior

Related Author

ANGPeng W

IUTian-shuang Q

IJing-chun L

ANHai-feng T

TIAN Jun-feng

ZHANG Chi

LIU Tao

LI Ning

Related Institution

Faculty of Electronic Information and Electrical Engineering,Dalian University of Technology

State Radio Monitoring Center

School of Information and Communication Engineering, Beijing University of Posts and Telecommunications

Institute of Computer Network Technology,Hebei University

河北大学数学与计算机学院

AI问答

⁰