I thought I'd share what has turned out to be a pretty effective spam filtering approach for me, and one that makes good use of a lot of Poco's features. It's a combination of approaches (whitelisting, bayesian filtering, and then challenge-response) and results in having to pay very little attention to the whole junkmail issue and inconveniencing very few unknown mail senders.
I've created a series of filters that flow as follows:
Filter 1: Sort all newsletters into a newsletters folder to read
Filter 2: Run poco's bayesian filter (but have the junk score threshshold set very high so that the message never gets moved based on the score). Add 100 to the junk score if Bayesian positive.
Filter 3: Stop processing if sender is known or domain is on the "approved domains" list (using the %addressbooks% and %exceptsenders% filter feature)
** ADDED ** Filter 4: Run the dns blacklist filter Hogyt put together. Add 100 to junk score if originating IP is black-listed.
Filter 5: Stop processing if Junk score less than 100. This means that it was Bayesian Negative and not DNS blacklisted.
Filter 6: Stop processing if the subject has a special code word
Filter 7: Otherwise, assume it's junk, and send an automated reply to the sender that says "Don't know who you are. If you're a real person, re-send your message with a code word in the subject line so I know you're not a spammer", and move it to the junk folder (or a quaratine folder). I send this from a different "postmaster" account that I've setup at hotmail so that the spammers don't get confirmation of my real email address.
Because of the whitelisting and bayesian filter steps, this approach means that less than 1 out of 1000 real senders get a bounce-back message, but almost all the spammers do and I never hear from them again.
I have a few other steps I include, which I won't go into detail about, but this is the crux of the approach. Overall, it's been very effective for me and I thought I'd post it for anyone else who might find it of interest.