SPAM BUSTER! Part 1 of 4

Let’s get back to the corporate world on spam fighting. Fortunately for many users sitting behind the computer screen, the jobs of fighting spams are left to the IT departments.
The problems here is that there are many companies in the markets providing anti spam solutions comprising of many difference package of solutions. So who do we choose? Many IT department brought anti appliance based on Sales talk. That is the greatest mistake, as a wrong appliance in place will cause much inconvenient on lost of emails, denial of services and lots of false positives. This blog is to help IT department on deciding the technologies best suitable for their environment.
I will not be listing the product brands and company names. Rather, I will list down the technologies available in the market, explain each of them and tell you which combination of the technologies is best in my point of view.

4 Type of key technologies uses in fighting Spam.

Filter – The old school method

Filter is commonly used by most anti spam appliances as one of their tools in blocking spam. Types of filters includes “Word list” or “Spam Dictionary”, “Black List” and “White list” of IP address, “Hash-Table” and “Bayesian spam filtering”. In my personal point of view, filter system are dangerous as it often result if high level of false positive rate especially in the early stage of implementation. It also required high level of user intervention due to the fast evolving changes in spam content and therefore need to fine tune the spam filter rules frequently.

Why did I say high level of false positive? Imagine that we use the word “SEX”. In most cases, “sex’ will be classified as a spam word. But if in the email that contain “Hi Joe, did you catch the show “Sex in the city” last night? This email will be block even though it is a harmless email between two friends. This are just one example, but you will be surprise to see common words listed in a default “spam dictionary” and you can imagine the numbers of mails to be blocked without an intensive level of fine tuning the “word list”.

While we are smart in adding in the key words appearing in the spam mail, Spammer are as good at modifying the words as well. I am pretty sure you people had seen “Viagra” to appear as “V1agr@”, ‘Vi@gra” or “V!agra”, etc. These words escape the “spam dictionary” and therefore result in false negative.

Filter system is effective with frequent fine tuning of the filtering system use. “Word list’, “Black list” of IP, etc must be updated frequently. Bear in mind that filter do not stop spam, it merely stop what you highlighted in your system. Even so, checking of misclassified email frequently is important to avoid missing of important mails.

End of Part 1