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Collin Tibbetts Phones & Addresses

    s
  • 11218 106Th Ave NE, Kirkland, WA 98033
  • Bellevue, WA
  • Seattle, WA
  • Los Angeles, CA
  • Hoquiam, WA
  • Kiona, WA

Publications

Us Patents

Stages, Phases In A Project Workflow

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US Patent:
20100299170, Nov 25, 2010
Filed:
May 19, 2009
Appl. No.:
12/468616
Inventors:
Alexandru Savescu - Issaquah WA, US
Samuel Chung - Kirkland WA, US
Pradeep GanapathyRaj - Bellevue WA, US
Collin Tibbetts - Seattle WA, US
John Lee Thoni - Seattle WA, US
Luke Humphrey - Issaquah WA, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06Q 10/00
US Classification:
705 8
Abstract:
A method is presented for creating a life cycle workflow for a project on a server computer. One or more workflow phases are created on the server computer. Each workflow phase corresponds to a plurality of workflow stages for the project. One or more workflow stages are created on the server computer. Each workflow stage corresponds to a specific sequence of workflow activities. One or more project detail pages are created on the server computer. Each project detail page is a web page that is made visible during the workflow stage. When a workflow stage is created, a workflow phase is selected to be associated with the workflow stage and one or more project detail pages are selected for the workflow stage.

Risk Assessment Modeling

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US Patent:
20160300059, Oct 13, 2016
Filed:
Jun 21, 2016
Appl. No.:
15/188639
Inventors:
- Redmond WA, US
David J. Steeves - Seattle WA, US
Robert Alexander Sim - Bellevue WA, US
Pui-Yin Winfred Wong - Redmond WA, US
Harry Simon Katz - Bellevue WA, US
Aaron Small - Seattle WA, US
Dana Scott Kaufman - Redmond WA, US
Adrian Kreuziger - Seattle WA, US
Mark A. Nikiel - North Bend WA, US
Laurentiu Bogdan Cristofor - Redmond WA, US
Alexa Lynn Keizur - Redmond WA, US
Collin Tibbetts - Seattle WA, US
Charles Hayden - Seattle WA, US
International Classification:
G06F 21/55
G06N 99/00
Abstract:
One or more techniques and/or systems are provided for risk assessment. Historical authentication data and/or compromised user account data may be evaluated to identify a set of authentication context properties associated with user authentication sessions and/or a set of malicious account context properties associated with compromised user accounts (e.g., properties indicative of whether a user recently visited a malicious site, created a fake social network profile, logged in from unknown locations, etc.). The set of authentication context properties and/or the set of malicious account context properties may be annotated to create an annotated context property training set that may be used to train a risk assessment machine learning model to generate a risk assessment model. The risk assessment model may be used to evaluate user context properties of a user account event to generate a risk analysis metric indicative of a likelihood the user account event is malicious or safe.

Risk Assessment Modeling

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US Patent:
20150339477, Nov 26, 2015
Filed:
May 21, 2014
Appl. No.:
14/283996
Inventors:
- Redmond WA, US
David J. Steeves - Seattle WA, US
Robert Alexander Sim - Bellevue WA, US
Pui-Yin Winfred Wong - Redmond WA, US
Harry Simon Katz - Bellevue WA, US
Aaron Small - Seattle WA, US
Dana Scott Kaufman - Redmond WA, US
Adrian Kreuziger - Seattle WA, US
Mark A. Nikiel - North Bend WA, US
Laurentiu Bogdan Cristofor - Redmond WA, US
Alexa Lynn Keizur - Redmond WA, US
Collin Tibbetts - Seattle WA, US
Charles Hayden - Seattle WA, US
International Classification:
G06F 21/55
G06N 99/00
Abstract:
One or more techniques and/or systems are provided for risk assessment. Historical authentication data and/or compromised user account data may be evaluated to identify a set of authentication context properties associated with user authentication sessions and/or a set of malicious account context properties associated with compromised user accounts (e.g., properties indicative of whether a user recently visited a malicious site, created a fake social network profile, logged in from unknown locations, etc.). The set of authentication context properties and/or the set of malicious account context properties may be annotated to create an annotated context property training set that may be used to train a risk assessment machine learning model to generate a risk assessment model. The risk assessment model may be used to evaluate user context properties of a user account event to generate a risk analysis metric indicative of a likelihood the user account event is malicious or safe.
Collin S Tibbetts from Kirkland, WA, age ~44 Get Report