Click-To-Call Gets A Wake Up Call

First, the firewall is exposed to its target environment to "learn" the particularities of Skype's traffic. Then, it uses the information collected together with pattern-matching techniques to actually identify Skype's related traffic.

Various technologies like neural networks, distributed statistical calculus, and pattern recognition through machine learning are involved in the methodology developed by Lynanda. These techniques are very similar to the ones currently used in financial statistics to discover regularities and typical patterns in apparently chaotic data like stock quotes.

The originality of the method is that it not only looks at the content of the network packets exchanged, it pays also attention to the timing at which they are sent and received. Given all this data, it is quite easy to get a footprint of the Skype application and drop its related traffic.

one challenge facing traffic-signature techniques on telecom networks is the high speed at which such pattern matching algorithms must be executed. Therefore, this filtering solution involves massively parallel computational capabilities as well as expensive database clusters.