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基于信息熵聚类的DDoS检测算法 被引量:3

DDoS Detection Algorithm Based on Cluster of Entropy
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摘要 采用信息熵进行DDoS特征表示,再采用K-means算法分析熵值,通过分析正常网络的分布规律,确定DDoS攻击检测的阈值,并根据阈值来更新正常行为的特征训练集或做出攻击响应。实验结果显示,这种方法可以快速完成训练与测试工作,能够有效检测DDoS攻击。 The entropy is used to represent the feature of DDoS, and the entropy is clustered by K-means algorithm. The threshold of DDoS detection is gotten from analyzing statistical normal network packets, then the normal characteristics training set is updated, and the DDoS is recognized on the basis of threshold. The experiments show that the measure can implement trainings and testing processes rapidly, and it can detect existence of DDoS effectively.
出处 《计算机系统应用》 2010年第12期164-167,共4页 Computer Systems & Applications
关键词 分布式拒绝服务 信息熵 K—means算法 distributed denial of service entropy K-means algorithm
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  • 1翟旭君,李春平.平行坐标及其在聚类分析中的应用[J].计算机应用研究,2005,22(8):124-126. 被引量:12
  • 2吴庆涛,张有根,邵志清.基于网络连接统计的分布式拒绝服务攻击检测[J].华东理工大学学报(自然科学版),2006,32(5):583-586. 被引量:4
  • 3宗兆伟,黎峰,翟征德.基于统计分析和流量控制的DNS分布式拒绝服务攻击的检测及防御[C].北京:2009全国计算机网络与通信学术会议.2009. 被引量:3
  • 4CNCERT/CC.2010互联网网络安全态势综述[R].2011. 被引量:1
  • 5Subbulakshmi T, Shalinie S M, Ramamoorthi A,Detcction and classification of DDoS attacks using machine learning algorithms[Y]. European Journal of Scientific Research, 2010,47 (3) : 334-346. 被引量:1
  • 6Wang Yao,Hu Mingzeng,Li Bin, et al.Tracking anomalous behav- iors of name servers by mining DNS traffic[C]//Lecture Notes in Computer Science,2006,4331:351-357,. 被引量:1
  • 7Rastegari S, Saripan M I, Rasid M F A.Detection of denial of service attacks against domain name system using neural net- works[J].IJCSI International Journal of Computer Science Issues, 2009( 1 ) : 23-27. 被引量:1
  • 8Xu Tu,He Dake,Zhcng Yu,Detecting DDoS attack based on one- way connection dcnsity[C]//Procecdings of 10th IEEE Internation- al Conference on Communication Systems,2006: 1-5. 被引量:1
  • 9CHEN S M,GUO C, YUAN X R, et al. OCEANS: online collaborative explorative analysis on network security[C]// Proceedings of the Eleventh Workshop on Visualization for Cyber Security. New York: ACM, Z014 : 1-8. 被引量:1
  • 10MCPHERSON J, MA K L, KRYSTOSK P, et al. PortVis: a tool for port-based detection of security events [C]//Pro- eeedings of the 2004 ACM Workshop on Visualization andData Mining for Computer Security. New York: ACM, 2004 : 73-81. 被引量:1

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