Bogo-Pogo AntiSPAM game

After a month I’ve been trying to contact one of my correspondent I get an autoreply saying: “Thank You for contacting me, but due to the increasing amount of spam I started to receive at this e-mail address, I decided to close it.”

Guess many people suffer of spam as they send all this excuses: “Hello, This email address is not monitored.”;
“Hello, You have contacted an email that is no longer checked.”;
“Due to a large amount of spam I no longer have time to wade through all of the email I receive to get to the legitimate messages. So if you have a need to contact me please do so at my helpdesk at…”.
 Others use various services like so you need to fill in a form with CAPTCHA to prove you’re not a spam-bot.

And now I thought why do I use the same email-address for 5 years without changing it or a spamarrest service?…
 Yes, I remember I was annoyed too much with spam last year. I had no a filter like spamassassin on my server and decided to create my own.
 My spam-filter script reads the mail-box on time basis and wipes spam emails out. It filters out Asian spam (with Content-Type like iso-2022-jp, iso-2022-kr, euc-kr, gb2312, ks_c_5601-1987 or Shift_JIS), some Watch, Bank and Pharm spam (with Rolex,Replica Watches, Royal,Regions,NatWest Bank and Drugs,Pills Pharma words). The script filtered:

400+ emails in May 07,
400+ in Jun 07,
500+ in Jul 07,
500+ in Aug 07,
400+ in Sep 07,
800+ in Oct 07,
600+ in Nov 07,
700+ in Dec 07,
700+ in Jan 08,
600+ in Feb 08,
1000+ in Mar 08 and
1200+ in Apr 08.

This reduced amount of spam by half. However I’m still getting spam into my inbox.


After I migrated to Kubuntu linux this year I was surprised with BogoFilter integrated with KMail application. BogoFilter detects spam almost like I were read it myself.

Bogofilter is a mail filter that classifies mail as spam or ham (non-spam) by a statistical analysis of the message’s header and content (body). The program is able to learn from the user’s classifications and corrections.
The statistical technique is known as the Bayesian technique and its use for spam was described by Paul Graham in his article A Plan For Spam in August 2002.

The real advantage of the Bayesian approach, of course, is that you know what you’re measuring. Feature-recognizing filters like SpamAssassin assign a spam “score” to email. The Bayesian approach assigns an actual probability. The problem with a “score” is that no one knows what it means. The user doesn’t know what it means, but worse still, neither does the developer of the filter.

KMail with Bogofilter

KMail provides you with 2 additional buttons: a circle with green recycle icon and a green tick. When you see a spam message in your inbox, click the recycle button to mark the message as spam. The Bogofilter analyses the message to learn from it and move it to the trash folder.
 So you have 2 buttons to delete emails now. The general “Del” button to delete old non-spam emails and the “Recycle” button to delete spam emails.

You also need to check your Trash (junk) folder for the first time to save non-spam emails. You click the green tick to let Bogofilter learn it’s not a spam. The Filter learns fast. After the first 2 weeks I didn’t see legitimate emails inside the junk folder.

All your custom filters work before the Bogofilter. So when you create a filter to move messages of your permanent correspondent into a separate folder, it works like a WhiteList for BogoFilter as well.
 You don’t need to manage a BlackList at all. The Bogofilter does it for you automatically.

Bogofilter is supported by Linux, FreeBSD, Solaris, OS X, HP-UX, AIX, RISC OS, SunOS, OS/2. But not by Windows…

Outlook with Junk Email filter

Outlook 2003 and 2007 include Junk Email filter that directs suspect messages to the Outlook Junk folder. The filter calculates “score” for a message to make decision it’s spam or not. You’re able to set the filter level from Low to High and manage “safe senders” and “blocked senders” lists.

Outlook with Spam Reader

There are many 3-rd party add-on’s for Outlook to filter spam emails. One of them looks similar to Bogofilter. Spam Reader uses the most reliable approach to spam filtering — Bayesian algorithm based on statistical analysis, capable to be adjusted to user’s needs and detect up to 98% of spam messages.

The Spam Reader provides you with additional buttons to train the filter.

If you work with Outlook Express you may want to take a look at yet another Bayes filter — Spam Bully.


by Michel Komarov, © Copyright 2008.


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