Tracking Blacklists

With the latest batch of additions today, I'm now tracking over 50 different blacklist zones for the newly revamped DNSBL Resource Blacklist Statistics Center. Thinking back to when I created the RRSS blacklist (the Radparker Relay Spam Stopper) in 1999, I am not sure there were even fifty anti-spam blacklist filters across the entire globe. Mine was definitely not the first, but I suspect that RRSS was probably one of the first ten.

Right now, I've got 13-week charts showing the effectiveness of 21 different blacklist zones. Look for public stats on additional lists soon, as I slowly compile effectiveness data on the lists I've just added. (And I've got even more tricks up my sleeve, so stay tuned!)

2 comments:

  1. I'm sure you must be aware of Jeff Makey's stats which go back all the way to 2001.

    I never really liked his set-up, because there was no notion of false positives, just a number of hits, but if nothing else, it's useful for reconstructing history.

    (See also -- ahem -- some real history ... this is on Archive.org, so allow for a good deal of database timeouts and frustrating reloads.)

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  2. Yeah, I'm a long time follower of Jeff's stats. It's good stuff. Part of what drove me to start my own monitoring is because stuff like Jeff's info is just hit rates, nothing on false positives or false negatives. As Jeff himself says:

    The results of this survey are not necessarily helpful for choosing a blacklist for the purpose of blocking spam. Such an evaluation would require good data on which of the thousands of e-mail messages handled by SDSC every week are truly spam and which are not, but if it were easy to automatically tell the difference we would just block the spam and not worry about blacklists. Without that data there can be no objective measure of a blacklist's effectiveness for blocking spam.

    This survey also does not attempt to measure the quality of blacklists in terms of erroneous listings (false positives) nor in terms of missing entries (false negatives) with respect to each blacklist's policy. To do so would require maintaining my own lists for comparison with the other blacklists, which would take far more effort than I am willing to expend.

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