White Papers for Gramm Leach Bliley Act (GLBA)

Combatting Image Spam

Borderware

Spam message volumes have doubled over the past 12 months and are expected to triple in the near future, so it is no wonder that end users are seeing twice as much uncaught spam in their inboxes. While the email filters are just as efficient as they were a year ago, they are dealing with twice the volume. This situation is worsened by the recent emergence of image spam. Through the BorderWare Security Network (BSN), it has been observed that image spam currently accounts for at least 35% of overall spam volumes and this trend is on the rise.The industry is seeing an evolution in spam attacks where many existing email filtering technologies are no longer effective. Users are being flooded with unwanted spam and are getting increasingly frustrated. What is needed are technologies that are adaptive and organizations that have the skill to understand and deal with these attacks. BorderWare’s Intercept™ Engine consistently delivers spam capture rates of over 97% and is capable of learning and adapting to new spam campaigns. Intercept uses a broad range of techniques to classify good mail and spam, including blocklists, sender reputation and behavior (based on BSN), textual analysis, and other heuristics. The recent emergence of image spam has presented new challenges and many of the existing anti-spam techniques are not as effective in detecting image spam. To help defeat these attacks, BorderWare developed Intercept Image Analysis a new patent-pending technology specifically designed to combat image spam.

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