Poisoning Complete-Linkage Hierarchical Clustering

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• 作者：Battista Biggio (20)
  Samuel Rota Bulò (21)
  Ignazio Pillai (20)
  Michele Mura (20)
  Eyasu Zemene Mequanint (20)
  Marcello Pelillo (22)
  Fabio Roli (20)
  
• 刊名：Lecture Notes in Computer Science
• 出版年：2014
• 出版时间：2014
• 年：2014
• 卷：8621
• 期：1
• 页码：42-52
• 全文大小：320 KB
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• 作者单位：Battista Biggio (20)
  Samuel Rota Bulò (21)
  Ignazio Pillai (20)
  Michele Mura (20)
  Eyasu Zemene Mequanint (20)
  Marcello Pelillo (22)
  Fabio Roli (20)
  
  20. University of Cagliari, Italy
  21. FBK-irst, Trento, Italy
  22. Ca-Foscari University, Venice, Italy
  
• ISSN：1611-3349

文摘

Clustering algorithms are largely adopted in security applications as a vehicle to detect malicious activities, although few attention has been paid on preventing deliberate attacks from subverting the clustering process itself. Recent work has introduced a methodology for the security analysis of data clustering in adversarial settings, aimed to identify potential attacks against clustering algorithms and to evaluate their impact. The authors have shown that single-linkage hierarchical clustering can be severely affected by the presence of a very small fraction of carefully-crafted poisoning attacks into the input data, highlighting that the clustering algorithm may be itself the weakest link in a security system. In this paper, we extend this analysis to the case of complete-linkage hierarchical clustering by devising an ad hoc poisoning attack. We verify its effectiveness on artificial data and on application examples related to the clustering of malware and handwritten digits.