Microsoft Technology Licensing, LLC

Fernando Gonzalez

Sanjib Saha

Janet Lynn Schneider

Frank Gorgenyi

Cristina Del Amo Casado

Stephen P DiAcetis

David Mahlon Hoover

Mark A Inderhees

Jonathan Matthew Kay

Lanny D Natucci, Jr

Stuart J Harper

Shaun C Hedrick

Parmjeet Singh

Hiep V Khuu

Ashish Vijay Gadre

Jyh-Han Lin

Chih-Wei Wang

Priyanka Bhargavi Vegesna

Daniel Estrada Alva

Stephen P Diacetis

Lanny D Natucci

Lanny D Natucci Jr

Techniques described herein provide multi-factor authentication based on positioning data. Generally described, configurations disclosed herein enable a system to authorize a particular action using positioning data, and possibly other data, associated with an identity. For example, when a user wishes to change a password or access a secured account, the system can authenticate a user if a device associated with the user is located in the secure area. The system can authenticate a user if a requested operation and/or a predetermined pattern of movement associated with the user is detected. For instance, the system allows the user to change the password when the user's computer has followed a predetermined pattern of movement, and when one or more verification procedures meets one or more criteria while the location of the computing device is within the predetermined area.

Multi-factor authentication using positioning data

Examples generate a route point radius for a geofence. A point of interest (POI) is identified. The coordinates for a route point on a navigational path associated with the POI is obtained. A distance from the coordinates of the route point to the POI is determined to generate a radius. An extension amount to encompass at least a portion of the navigational path is added to the radius to generate a route point radius. A contextual environment of a user traveling on the navigational path is utilized to adjust the route point radius. The contextual environment includes the mode of travel and/or the direction of travel of the user. A geofence is generated based on at least one route point radius associated with the POI. An alert is triggered when a user crosses a perimeter of the geofence encompassing the portion of the navigational path.

Defining a contextual geofence

The location of a computing device is determined, and the location of an area of interest that is a geographic area referred to as a geo-fence is identified. The accuracy of the determined location of the computing device has an associated uncertainty, so the exact position of the computing device cannot typically be pinpointed. In light of this, the uncertainty associated with the determined location is evaluated relative to the size of the geo-fence in order to determine whether the computing device is inside the geo-fence or outside the geo-fence. Based on this determination, various actions can be taken if the user is entering the geo-fence, exiting the geo-fence, remaining in the geo-fence for at least a threshold amount of time, and so forth.

Detecting geo-fence events using varying confidence levels

A device location is determined, and the location of an area of interest that is a geographic area referred to as a geo-fence is identified. Multiple geo-fences can be identified by the device, and different geo-fences can be associated with different programs on the device. An operating system of the device implements multiple different periods of operation for the device, including a conservation period during which certain programs are not typically scheduled to run, and an execution period during which such programs are typically scheduled to run. A system identifies geo-fence events, which occur when the device enters or exits the geo-fence. The system maintains a record of the geo-fence events for each of multiple geo-fences, and provides to a program selected ones of those geo-fence events at a time when the program is scheduled to run on the device during an execution period of the operating system.

Coalescing geo-fence events

A computing device includes at least one processor and a memory, the memory storing computer-executable instructions for causing the device to be configured to load a subset of geo-fences from secondary storage to primary storage for tracking by the computing device, the subset of geo-fences selected from a set of available geo-fences stored in the secondary storage, based on a selection criteria. The computing device further creates a boundary geo-fence with a radius corresponding to a distance between a current location of the computing device and an edge of a geo-fence in the subset of geo-fences that is furthest from the current location of the computing device. Upon detecting a geo-fence event associated with a new location of the computing device in relation to the boundary geo-fence, a new subset of geo-fences is re-loaded, and a new boundary geo-fence is created based on the new location of the computing device.

Scalability and reliability of hardware geo-fencing with failover support

A determination of whether a mobile computing device is indoors or outdoors can incorporate any of a variety of factors to make an efficient and accurate determination of indoor-outdoor status. Such a status can be useful for use in conjunction with positioning services. Features such as bounding boxes, activity determination, and the like can be used to strike a balance between power consumption and accuracy. A positive user experience with fewer false detections can result.

Accounting for indoor-outdoor transitions during position determination

Systems and methods disclosed herein may include tracking one or more geo-fences using a GNSS hardware processor within a computing device. The tracking may use at least one GNSS signal. State changes of the one or more geo-fences during the tracking may be saved in a shared state database. The shared state database may be shared between the GNSS hardware processor and an application processor within the computing device. Upon detecting a deterioration of the at least one GNSS signal, tracking the one or more geo-fences may be switched from using the GNSS hardware processor to using the application processor. After the switching, an initial state of each of the one or more geo-fences may be set by using states currently stored in the shared state database prior to the switching.

Improving scalability and reliability of hardware geo-fencing with failover support

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Bellevue, WA, United States of America

Fernando Gonzalez