Aaron Justin Wong Small

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.

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.