Barracuda Spam Firewall
Complex system, which includes SPAM – filter, virus – filter capability for protection from Spoofing, Phishing and Spyware as well as from attack which do denial of services (Denial of Service) for the e-mail of the company.Barracuda Spam Firewall includes variety of anti spam technologies, among which are Black Listing of Web sites & domains (List of the most aggressive spammers and sites source of spam. They are supported and renewed jointly by Barracuda and other organizations); Message content scoring (System for measuring the possibility of one received message to be spam. The decision is taken on the basis of different factors, result of putting in practice the eristic techniques for researching the message.); Checksum technology (System for tracking for repentance in the content of one message in Internet. It can be taken as SPAM, if it appears regularly for certain time period from different sources), as well as Message authenticity checking (set of algorithms based on the SMTP protocol giving the opportunity to check, if one message is coming from safe source or not.).
Among the functionalities of Barracuda Spam Firewall are also algorithms from the type Blacklists and Whitelists, which allow the categorization of IP addresses, mail addresses and domains in lists, for which there could be applied different policies (BLOCK, QUARANTINE, PASS). It is also important that the policies can be applied separately for every customer according to the essence of his work and his behavior in the network.
Barracuda Spam Firewall is typical example of self-learning intelligent solution of new generation. It uses Bayesian algorithm for predicting of future events on the base of analyses of past events. Developed by Thomas Bayes(1702-1761), it is eristic algorithm, which analyzes the content of every received message. The evaluation of the SPAM probability is given on the basis of compartment with patterns, to which the algorithm has been learned. This algorithm is the most accurate modern method for SPAM identification and in the same time it is one of the most innovative technologies used in this segment of the informational security. The usage of Bayesian Algorithm allows learning for acquiring maximal accuracy of identification and personalization – individual base for every customer can be made.
