Microsoft Technology Licensing, LLC

Chad W Mills

Ryan Charles Colvin

Robert L McCann

Robert Alexander Sim

Joshua Korb

Scott Laufer

Sung Chung

Eliot Carleton Gillum

Krishna C Vitaldevara

Kristofer Noel Iverson

Xin Huang

Aleksander R Kolcz

Jason D Walter

Malcolm Hollis Davis

Douglas John Hines

Mehrdad Bidgoli

Geoff Hulten

John Scarrow

Kevin Andrew Chan

Harry Simon Katz

Elliott Jeb Haber

Milenko Drinic

Ameya S Bhatawdekar

Eriola Kruja

Robert Lee Mccann

Joshua David Korb

In one embodiment, a human interactive proof portalmay use a biometric input to determine whether a user is a standard user or a malicious actor. The human interactive proof portalmay receive an access requestfor an online data servicefrom a user device. The human interactive proof portalmay send a proof challengeto the user devicefor presentation to a user. The human interactive proof portalmay receive from the user devicea proof responsehaving a biometric metadata descriptionbased on a biometric input from the user.

Using the ability to speak as a human interactive proof

A system and method of managing unsolicited email sent to an email system over a network. Email messages are received at an message at an inbound mail transfer agent. A determination is made as to whether the email message is suspected to be an unsolicited suspect message. One or more queries for additional information on one or more characteristics of the message is initiated. Determinations are made based on replies to the queries before issuing a message accepted for delivery indication to a sending server.

Real-time spam look-up system

A reputation based redirection service is usable to build URL wrappers for un-trusted and unknown URLs. Such URL wrappers can be used to protect Web users by, for example, redirecting traffic to interstitial Web pages. Additionally, reputation decisions can be made by the service to further protect users from malicious URLs.

Reputation based redirection service

Detecting spam from metafeatures of an email message. As a part of detecting spam, the email message is accessed and a distribution of numerical values is accorded to a set of features of the email message. It is determined whether the distribution of numerical values accorded the set of features of the email message is consistent with that of spam. Access is provided to the determination of whether the email message has a distribution of numerical values accorded the set of features that is consistent with that of spam.

Detecting spam from metafeatures of an email message

Determining email filtering type based on sender classification. Incoming email is accessed and a sender of the incoming email is identified. The reputation of the sender of the incoming email is determined. An email sender classification is made based on the reputation of the sender. A determination of the type of filtering operations to be performed by an email filter on the email is made based on the classification. The parameters of the type of filtering operations to be performed are determined. The parameters of the type of filtering operations to be performed are provided to the email filter.

Determining email filtering type based on sender classification

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Redmond, WA, United States of America

Chad W Mills