We compare two statistical methods for identifying spam or junk electronic mail. Spam filters are classifiers which determine whether an email is junk or not. The proliferation ...
The "conversion rate" of spam -- the probability that an unsolicited e-mail will ultimately elicit a "sale" -- underlies the entire spam value proposition. How...
Chris Kanich, Christian Kreibich, Kirill Levchenko...
Gray mail, messages that could reasonably be considered either spam or good by different email users, is a commonly observed issue in production spam filtering systems. In this pa...
In this paper we consider the approach to image spam filtering based on using image classifiers aimed at discriminating between ham and spam images, previously proposed by other a...
Giorgio Fumera, Fabio Roli, Battista Biggio, Ignaz...
We describe experiments with a Naive Bayes text classifier in the context of anti-spam E-mail filtering, using two different statistical event models: a multi-variate Bernoulli ...