Concordia University researchers have developed a method for removing unwanted spam emails from user inboxes. The method is based on a new statistical framework for spam filtering that the researchers say quickly and efficiently blocks unwanted messages. "By considering patterns from text and images simultaneously, we've been able to propose a new method for filtering out spam," says Concordia's Ola Amayri.
Spam messages often use sophisticated tricks, such as deliberately obscuring text, combining words with symbols, and using groups of the same images with different backgrounds and colors that might contain random text from the Web. When these tricks are used together, conventional spam filters are unable to stop the messages because they focus on either text or images but rarely both.
"Our new method for spam filtering is able to adapt to the dynamic nature of spam emails and accurately handle spammers' tricks by carefully identifying informative patterns, which are automatically extracted from both text and images content of spam emails," Amayri says.
From Concordia University
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Abstracts Copyright © 2012 Information Inc., Bethesda, Maryland, USA
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