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  • 标题:P2P Botnet Detection Based on Nodes Correlation by the Mahalanobis Distance
  • 本地全文:下载
  • 作者:Zhixian Yang ; Buhong Wang
  • 期刊名称:Information
  • 电子版ISSN:2078-2489
  • 出版年度:2019
  • 卷号:10
  • 期号:5
  • 页码:160-175
  • DOI:10.3390/info10050160
  • 出版社:MDPI Publishing
  • 摘要:Botnets are a common and serious threat to the Internet. The search for the infected nodes of a P2P botnet is affected by the number of commonly connected nodes, with a lower detection accuracy rate for cases with fewer commonly connected nodes. However, this paper calculates the Mahalanobis distance—which can express correlations between data—between indirectly connected nodes through traffic with commonly connected nodes, and establishes a relationship evaluation model among nodes. An iterative algorithm is used to obtain the correlation coefficient between the nodes, and the threshold is set to detect P2P botnets. The experimental results show that this method can effectively detect P2P botnets with an accuracy of >85% when the correlation coefficient is high, even in cases with fewer commonly connected nodes.
  • 关键词:P2P botnet; Mahalanobis distance; correlation coefficient P2P botnet ; Mahalanobis distance ; correlation coefficient
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