Researchers have proposed a new statistical framework for spam filtering
that can quickly and efficiently block unwanted messages in your email
inbox.
Scientists from the Concordia University have conducted a
comprehensive study of several spam filters in the process of developing
a new and efficient one.
"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," said researcher Ola Amayri in a statement.
Until now, the
majority of research in the domain of email spam filtering has focused
on the automatic extraction and analysis of the textual content of spam
emails and has ignored the rich nature of image-based content.
When
these tricks are used in combination, traditional spam filters are
powerless to stop the messages, because they normally focus on either
text or images but rarely both, the study found.
"The majority of
previous research has focused on the textual content of spam emails,
ignoring visual content found in multimedia content, such as images. By
considering patterns from text and images simultaneously, we've been
able to propose a new method for filtering out spam," said researcher
Ola Amayri.
Amayri explained that new spam messages often employ
sophisticated tricks, such as deliberately obscuring text, obfuscating
words with symbols, and using batches of the same images with different
backgrounds and colours that might contain random text from the web.
By
conducting extensive experiments on traditional spam filtering methods
that were general and limited to patterns found in texts or images, the
new method is much stronger, based on techniques used in pattern
recognition and data mining, to filter out unwanted emails.
Although the new method has been tested on English spam emails, Amayri said it can be easily extended to other languages.
"Spammers
keep adapting their methods so that they can trick the spam filters.
Researchers in this field need to work together to keep adapting our
methods too, so that we can keep spam out and focus on those messages
that are really important," Amayri added.