Microsoft Technology Licensing, LLC

Jay T Buckingham

Robert L Rounthwaite

Joshua T Goodman

Geoffrey John Hulten

Paul Stephen Rehfuss

David Maxwell Chickering

Eliot Carleton Gillum

John D Mehr

Anthony Paul Penta

Ryan Charles Colvin

Gopalakrishnan Seshadrinathan

Identification of email forwarders is described. In an implementation, a method includes using heuristics to identify email forwarders for use in a reputation system for locating spammers. In another implementation, a method includes determining a likelihood that a particular Internet Protocol (IP) address corresponds to an email forwarder and processing email originating from the particular IP address based on the determined likelihood. In a further implementation, a method includes collecting heuristic data that describes characteristics of emails sent from one or more Internet Protocol (IP) addresses and constructing a model from the heuristic data for identifying whether at least one of the IP address is an email forwarder. In yet a further implementation, a method includes identifying that a particular Internet Protocol (IP) address likely corresponds to an email forwarder and processing email from the particular IP address based on an implied sender of the email.

Identification of email forwarders

Email spam filtering is performed based on a sender reputation and message features. When an email message is received, a preliminary spam determination is made based, at least in part, on a combination of a reputation associated with the sender of the email message and one or more features of the email message. If the preliminary spam determination indicates that the message is spam, then a secondary spam determination is made based on one or more features of the received email message. If both the preliminary and secondary spam determinations indicate that the received email message is likely spam, then the message is treated as spam.

Using message features and sender identity for email spam filtering

Network domain reputation-based spam filtering is described. In an embodiment, emails are received from a network domain and a reputation of the network domain is established. Additional emails are filtered as they are received to determine a status of each email as spam email or not spam email. An email can be determined to be a spam email based on any one or more of the reputation of the network domain, an authentication status of an email, and other information that can be derived from an email.

Network domain reputation-based spam filtering

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Kirkland, WA, United States of America

Jay T Buckingham