A Game Theoretical Model for Adversarial Learning

  title={A Game Theoretical Model for Adversarial Learning},
  author={Wei Liu and Sanjay Chawla},
  journal={2009 IEEE International Conference on Data Mining Workshops},
It is now widely accepted that in many situations where classifiers are deployed, adversaries deliberately manipulate data in order to reduce the classifier’s accuracy. The most prominent example is email spam, where spammers routinely modify emails to get past classifier-based spam filters. In this paper we model the interaction between the adversary and the data miner as a two-person sequential noncooperative Stackelberg game and analyze the outcomes when there is a natural leader and a… CONTINUE READING



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