 The spammer hopes that the addition of random (or even carefully selected) words that are unlikely to appear in a spam message will cause the spam filter to believe the message to be legitimate—a statistical type II error.Spammers also hope to cause the spam filter to have a higher false positive rate by turning previously innocent words into spammy words in the Bayesian database (statistical type I errors) because a user who trains their spam filter on a poisoned message will be indicating to the filter that the words added by the spammer are a good indication of spam.At the Spam Conference held at MIT in 2004 John Graham-Cumming presented two possible attacks on POPFile's Bayesian engine.