期刊文献+

动态僵尸网络模型研究 被引量:2

Research of dynamic Botnet model
下载PDF
导出
摘要 现有的僵尸网络技术和检测方法通常局限于某种特定的僵尸网络。为提高僵尸网络的隐秘性,提出了一种动态僵尸网络模型,利用有向图进行描述,可以表示不同类型的僵尸网络。对模型的暴露性、可恢复性和可持续性等动态属性进行量化分析,给出了一种僵尸主机主动丢弃原则。实验结果表明,提出的方法可以有效降低僵尸网络检测率,提高僵尸网络的可持续性和可恢复性。 The existing Botnet techniques and detection methods are usually confined to specific Botnet.To improve the confidentiality of Botnet,the authors proposed a dynamic Botnet model described with directed graph,which can accommodate various Botnets.Several dynamic attributes of the proposed model were analyzed,such as exposedness,resilience,sustainability in detail,and then a bot abandon policy was presented.The experimental results indicate that the proposed method can decrease the Botnet's detection ratio and improve sustainability and resilience effectively.
出处 《计算机应用》 CSCD 北大核心 2010年第3期692-694,共3页 journal of Computer Applications
关键词 僵尸网络 僵尸主机 有向图 丢弃原则 检测率 Botnet Bot directed graph abandon policy detection ratio
  • 相关文献

参考文献9

  • 1诸葛建伟,韩心慧,周勇林,叶志远,邹维.僵尸网络研究[J].软件学报,2008,19(3):702-715. 被引量:157
  • 2SYMANTEC INC.Symantec's global Internet security threat report[R],2008.
  • 3BANDAY M T,QADRI J A,SHAH N A.Study of Botnets and their threats to Internet security[EB/OL].[2009-08-25].http://sprouts.aisnet.org/9-24.
  • 4WANG P,SPARKS S,ZOU C C.An advanced hybrid peer-to-peer Botnet[C]// Proceedings of the 1st Workshop on Hot Topics in Understanding Botnets.Cambridge,Massachusetts:USENIX Association,2007:2-2.
  • 5STRAYER W T,LAPSELY D,WALSH R,et al.Botnet detection countering the largest security threat[M].New York:Springer,2008.
  • 6RAMACHANDRAN A,FEAMSTER N,DAGON D.Revealing Botnet membership using DNSBL counter-intelligence[C]// Proceedings of the 2nd Conference on Steps to Reducing Unwanted Traffic on the Internet.San Jose:USENIX Association,2006:49-54.
  • 7ENDICOTT-POPOVSKY B,NARVAEZ J,SEIFERT C,et al.Use of deception to improve client honeypot detection of drive-by-download attacks[C]// Proceedings of the 5th International Conference on Foundations of Augmented Cognition Neuroergonomics and Operational Neuroscience.Berlin:Springer,2009:138-147.
  • 8RAMACHANDRAN A,SEETHARAMAN S,FEAMSTER N,et al.Monitoring stealthy network conversations with sampled traffic[EB/OL].[2009-08-15].http://www.hacker-soft.net/tools/Defense/tr-detecting06.pdf.
  • 9MASUD M M,AL-KHATEEB T,KHAN L,et al.Flow-based identification of Botnet traffic by mining multiple log files[C]// Proceedings of the 1st International Conference on Distributed Framework and Applications.Washington,DC:IEEE Computer Society,2008:200-206.

二级参考文献4

共引文献156

同被引文献36

引证文献2

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部