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Topic: #Bayesian-models

Defeating Bayesian Spam Filters

2018-03-07⊺16:20:00-06:00

This 2005 paper is a kind of precursor to the current literature about adversarial examples: It shows how to modify an e-mail that a naive Bayesian spam filter correctly classifies as spam so as to induce the same filter to misclassify it as ham. The modification consists in replacing a small number of words.

“Adversarial Learning”
Daniel Lowd and Christopher Meek, ACM Conference on Knowledge Discovery and Data Mining, August 2005
https://ix.cs.uoregon.edu/~lowd/kdd05lowd.pdf

#adversarial-examples #spam-filters #Bayesian-models

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John David Stone (havgl@unity.homelinux.net)

created June 1, 2014 · last revised December 10, 2018