Symantec Corporation

Eli Mantel

Art Medlar

David Hoogstrate

Ken Schneider

Sandy Jensen

Matt Gleeson

Sanford Jensen

A method and system for filtering email spam using email noise reduction are described. In one embodiment, the method includes detecting, in an email message, data indicative of noise added to the email message to avoid spam filtering. The method further includes modifying the content of the email message to reduce the noise, and comparing the modified content of the email message with the content of a spam message.

Method and apparatus for filtering email spam using email noise reduction

A similarity measurement manager uses n-gram analysis to identify spam email messages. The similarity measurement manager tokenizing an email message into a plurality of overlapping n-grams, wherein n is large enough to identify uniqueness of artifacts. The similarity measurement manager employs feature selection by comparing the created n-grams to n-grams of known artifacts which were created according to the same methodology. Created n-grams that match an n-gram of a known artifact are ignored. The similarity measurement manager compares the remaining created n-grams to pluralities of n-grams of known spam email messages, the n-grams of the known spam email messages being themselves created by executing the same steps. The similarity measurement manager determines whether the email message comprises spam based on whether or not the n-gram comparison indicates that it is substantially similar to a known spam email message.

Spam email detection based on n-grams with feature selection

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Palo Alto, CA, United States of America

Eli Mantel