Using Machine Teaching to Identify Optimal Training-Set Attacks on Machine Learners

@inproceedings{Mei2015UsingMT,
  title={Using Machine Teaching to Identify Optimal Training-Set Attacks on Machine Learners},
  author={Shike Mei and Xiaojin Zhu},
  booktitle={AAAI},
  year={2015}
}
We investigate a problem at the intersection of machine learning and security: training-set attacks on machine learners. In such attacks an attacker contaminates the training data so that a specific learning algorithm would produce a model profitable to the attacker. Understanding training-set attacks is important as more intelligent agents (e.g. spam filters and robots) are equipped with learning capability and can potentially be hacked via data they receive from the environment. This paper… CONTINUE READING
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