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Anti-Spam

No single analytic technique is enough to stop the constantly morphing forms of spam. Even multiple techniques are not enough to keep spam at bay for long. And rigid scoring often ends up blocking e-mail that you actually want to receive. SonicWALL takes spam management beyond arbitrary scoring with our revolutionary evidence evaluation system that identifies the sender, analyzes the content, and applies a collaborative review to every e-mail. These methods are 98 percent effective at stopping spam. Only when all three elements are simultaneously cross-analyzed can you have true confidence in your solution's handling of your company's e-mail.

Cross Analysis

Sender, content, and collaborative review are each excellent spam identifiers. But if only a single method is used, the risk of false positives increases. However, SonicWALL's unique cross-analysis requires that at least two of our independent techniques label a message as spam before it is marked as definite spam, ensuring no good e-mail is caught.

Sender Authentication and Reputation

The techniques in this category identify e-mails that falsify their origin and check the reputation of the e-mail sender. Using both Sender ID Framework and SonicWALL Reputation™, the SonicWALL solution not only validates the sender's claimed identity but also evaluates that sender's reputation.

Sender ID provides an important part of the anti-spam solution by identifying e-mails that have inconsistencies between the claimed origin and actual origin. SonicWALL leads its industry by incorporating this newly-adopted security standard into its product.

Spam can come from domains or addresses that are valid for the claimed domains, which means that Sender ID analysis is not enough. With the added technique of SonicWALL Reputation^TM, SonicWALL's anti-spam analysis not only validates the claimed origin of the e-mail through Sender ID, but also assesses whether the sender has a good or bad reputation for sending spam e-mails by cross-checking against SonicWALL's proprietary database—the industry's largest—with over 20 million entries to date.

Content Analysis

Naïve Bayesian rules don't meet the challenge of today's pervasive spammer. Spammers use many techniques to confuse naïve Bayesian filters into letting the spam messages through. SonicWALL's Adversarial Bayesian^TM is designed for this environment. SonicWALL's Adversarial Bayesian uses a variety of techniques, including Lexigraphical Distancing, which finds variations of spam words, and Jibberish Detection, which detects strings of nonsense text often found in spam. SonicWALL's Adversarial Bayesian offers the industry's most comprehensive content review.

Collaborative Network

SonicWALL Self Monitoring Active Response Team (SMART) Network^TM is a real-time network of over one million global users whose responses enable SonicWALL to determine how to quickly identify and react to new spam trends. In addition, since this network gets “real” e-mail, SonicWALL SMART Network also understands legitimate e-mail, dramatically reducing the false positive rate. SonicWALL immediately applies the results of its analysis through SonicWALL SMART Network, passing the knowledge and value of its collaborative network to its customers in real time.

Notification of User Actions

E-mail can be delivered to a given user based on a specific action that user took such as unjunking the e-mail or having added the sender of the e-mail to the user’s allowed list. SonicWALL Email Security allows the administrator to automatically tag those emails that bypass spam filtering based on the action of the user receiving the message. This “tag” is appended on to the e-mail’s Subject so it can clearly be identified as being allowed by the user. For example, if a spam e-mail is delivered to the user because the sender is on the user’s allowed list, the Subject is pre-pended with [Junk released by allowed list].

Result: No Spam & Headache-Free E-mail

Our unique, independent cross-analysis combined with Personalized Spam Management, succeeds because it provides an absolute judgment of definite and likely spam, and handles individual user preferences. The result is a judgment that lets you confidently delete unwanted e-mail, securely quarantine suspect e-mail, and accurately receive “good” e-mail.