07-Sep-10 09:04:03
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Assessment

	Very good
	Satisfying
	Incomprehensible

From Sebastian Altepost

The digital finger print is fraud resistant

More than 80% of all eMails are spam. No problem at all with the Message Identification Services for David.zehn!. That is, because the MIS do not only work in a completely different way and are more reliable than any conventional spam filter: The MIS are perfectly integrated into David.zehn!, easily activated and completely maintenance-free. And best of all: You are now able to put this practical service to the acid test for four weeks, completely free of charge and without any commitments.

Spam filters are obsolete
The different spam detection methods of conventional spam filters rely on the basis of so-called Black- and Whitelist, Content-Check or the Bayes-Filter-Method. Due to the high amount of spam messages and the clever brain of the spam senders, those methods are not sufficient anymore. The disadvantages become apparent very fast:

Black-, Whitelist
Black- and Whitelists just block (Blacklist) or accept (Whitelist) eMails from defined domains, eMail addresses or IP addresses. But the following issues are not being considered:
• eMail- and IP adresses of spam senders permanently change
• eMails from mail servers with dynamic IP addresses will often be blocked
• High administrative effort to keep the lists up-to-date
• Spam senders are using security leaks of companies to send spam from legitimate addresses

Content-Check
The Content-Check method searches the message for spam typical key words. If one of these words, for instance "Viagra", is found in an eMail, the message will automatically be classified as spam, But this method also does not bring any satisfying results:
• This kind of filter can be outwitted easily by using a different spelling
• Real eMails containing one of these words will be classified as spam
• eMails with integrated links or HTML format will often be identified wrongly as spam
• Pictures (and their content) will not be identified as spam

Bayes-Filter-Method
This is a so-called self-learning filter method. The user has to sort nearly 1.000 eMails manually while it creates automatic filter rules. Disadvantages of this method:
• Permanent and very high administrative effort
• High error potential

The worst case, which can become true with all these filter methods, is that real eMails will be wrongly identified as spam messages. Due to this fatal mistake, caused by the filter's so-called "False-Positive-Rate", a lot of important business information will get lost in the enormous amount of spam eMails. This will additionally cost precious time, cash and especially nerves.

Rely on the Message Identification Services
Besides an optimal spam identification rate, a really excellent system is characterized by the fact it will not identify the remaining 20% of "clean" eMails as spam. The Trust-Center-principle have proved to be the only reliable method, that the Message Identification Services by Tobit.Software are also based on:

No more False Positives: Thanks to the reliable check by a central server

• No distinguishing between spam or no spam, but specified classification into different categories (Spam, Clean eMail, Broadcast, etc.)
• "False-Positives" are conceptually impossible due to the individual check and categorization

Convince yourself
The best way is to convince yourself of the functionality of the MIS by putting this service to the acid test for four weeks completely for free and without any commitments.

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