Proofpoint, Inc.

Charles Wade Chambers

David Eric Hagar

Martin Traverso

Dain Sidney Sundstrom

Mark Erol Kent

David Andrew Phillips

Dynamically detecting abnormalities in otherwise legitimate emails containing Uniform Resource Locators (URLs) is provided. An example method includes determining one or more rules defining normal patterns in a number of sending Top-Level Domains of previously received emails received via a computer network to a user or group of users; generating a trusted trends criteria for a received email, associated with the user or the group of users, by evaluating the received email against the one or more rules; determining whether the trusted trends criteria exceeds a predetermined threshold; in response to exceeding the predetermined threshold, generating a second URL and applying it to the received email by replacing a first URL of the received email with the second URL; and redetermining the one or more rules defining normal patterns in the number of sending Top-Level Domains based on the previously received emails and the received email.

Dynamically detecting abnormalities in otherwise legitimate emails containing uniform resource locators (URLs)

A method for filtering unsolicited emails may comprise dynamically aggregating historical email data associated with a user or a group of users and dynamically determining one or more trusted trends criteria associated with the historical email data. The method may further comprise receiving a new email addressed to the user or the group of users, calculating a score associated with the new email based on the one or more trusted trends criteria, determining that the score is above a predetermined threshold score, and, based on the determination, selectively filtering the new email.

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Sunnyvale, CA, United States of America

Charles Wade Chambers