Revised Naive Bayes classifier for combating the focus attack in spam filtering
Junyan Peng, Patrick P. K. Chan · 2013
The focus attack, which misleads the classifier to block the legitimate emails containing particular words from the user, is the causative adversary attack in the spam filter application. This paper proposes the revised Naive Bayes classifier to combat the focus attack. For each feature in the Naive Bayes classifier, the additional weight based on the number of ham and spam containing the feature is added. The weight reduces the effect of the focus attack to the features. Experimental results show that the proposed method is more robust under the focus attack. The accuracy on the attacked samples of the proposed method is higher than standard Naive Bayes classifier, especially when the degree of attack is large.