Researchers Propose Spam Filter That Screens Visual Content In Conjunction with Text
Researchers at Concordia University's Institute of Information Systems Engineering are working on a new statistical framework for spam filtering that addresses the shortcomings of present systems. Most current approaches focus either on the text in messages or the image saturation, but rarely both text and image. The method proposed by researchers examines the image content along with the text, to thwart the image layering and other tactics used by spammers to sneak messages through filters. "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," says PhD candidate Ola Amayri who is leading the study.
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