Human Mobility Rule-Based Device Location Tracking

• US 20140378066A1
• Filed: 06/24/2013
• Published: 12/25/2014
• Est. Priority Date: 06/24/2013
• Status: Active Grant

• Current Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Original Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Inventors: Liu, Hui, Pandey, Santosh, Zhu, Jiang
• Granted Patent: US 9,565,584 B2
• Time in Patent Office: Days
• US Class Current: 455/67.11
• CPC Class Codes: H04W 24/04 Arrangements for maintaining operational condition
• CPC Class Codes: H04W 24/08 Testing, supervising or monitoring using real traffic
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 48/04 based on user or terminal location or mobility data, e.g. moving direction, speed
• CPC Class Codes: H04W 64/003 locating network equipment

Abstract

Techniques are presented herein to provide human mobility pattern based modeling and tracking of a group of network enabled user devices associated with the same person. An association is made, at a tracking device, between a plurality of user devices and a user. Location information for each of the plurality of user devices is derived through network activity of the plurality of user devices. Locations for the plurality of user devices are derived from the location information. One or more predetermined user mobility pattern rules are applied to the plurality of user devices. User anomalies are detected when the tracked locations indicate that one or more of the plurality of user devices has violated one or more the predetermined user mobility rules.

Claims

1. A method comprising:

associating, at a tracking device, a plurality of network enabled user devices with a user;

deriving location information for each of the plurality of user devices through activity of the plurality of the user devices on a network;

tracking locations for the plurality of user devices from the derived location information;

applying one or more predetermined user mobility pattern rules to the plurality of user devices; and

detecting user anomalies when the tracked locations indicate that one or more of the plurality of user devices has violated one or more the predetermined user mobility rules.

2. The method of claim 1, wherein associating the plurality of user devices with the user comprises determining that one or more of the plurality of user devices has logged into the network with a login associated with the user.

3. The method of claim 1, wherein associating the plurality of user devices with the user comprises clustering the plurality of user devices based on mobility cross entropy.

4. The method of claim 1, further comprising determining device type for each of the plurality of user devices.

5. The method of claim 1, wherein applying the one or more predetermined user mobility rules comprises applying a rule indicating that mobile user devices associated with the user, when changing location, are located with the user.

6. The method of claim 1, wherein applying the one or more predetermined user mobility rules comprises applying a rule indicating that mobile devices associated with the user may change location, but two or more of the mobile devices cannot simultaneously move in different directions when changing location.

7. The method of claim 1, further comprising determining a main location of the user in response to tracking locations for each of the plurality of user devices.

8. The method of claim 7, wherein applying the one or more predetermined user mobility rules comprises applying a rule indicating that when two or more mobile devices move from the main location of the user, the two or more mobile devices will return to the main location at the same time.

9. The method of claim 1, further comprising disabling network access for one or more of the plurality of user devices in response to detecting user anomalies.

10. The method of claim 1, further comprising sending a message to a first of the plurality of user devices in response to determining a user anomaly associated with a second of the plurality of network enable devices.

11. The method of claim 1, further comprising transferring application services from a first of the plurality of user devices to a second of the plurality of user devices in response to determining a user anomaly associated with the first of the plurality of network enable devices.

12. The method of claim 1, wherein tracking locations for the plurality of user devices comprises applying density based location tag partitioning to the location information.

13. An apparatus comprising:

a network interface unit configured to enable network communications;

a memory; and

a processor coupled to the network interface unit and the memory, wherein the processor is configured to;

associate a plurality of network enabled user devices with a user;

derive location information for each of the plurality of user devices through activity of the plurality of the user devices on a network;

track locations for the plurality of user devices from the derived location information;

apply one or more predetermined user mobility pattern rules to the plurality of user devices; and

detect user anomalies when the tracked locations indicate that one or more of the plurality of user devices has violated one or more the predetermined user mobility rules.

14. The apparatus of claim 13, wherein the processor is further configured to associate the plurality of user devices with the user through determining that one or more of the plurality of user devices has logged into the network with a login associated with the user.

15. The apparatus of claim 13, wherein the processor is further configured to associate the plurality of user devices with the user through clustering the plurality of user devices based on mobility cross entropy.

16. The apparatus of claim 13, wherein the processor is further configured to track locations for the plurality of user devices by applying density based location tag partitioning to the location information.

17. A tangible, non-transitory computer readable medium comprising instructions that when executed by a processor cause the processor to:

associate a plurality of network enabled user devices with a user;

derive location information for each of the plurality of user devices through activity of the plurality of the user devices on a network;

track locations for the plurality of user devices from the derived location information;

apply one or more predetermined user mobility pattern rules to the plurality of user devices; and

detect user anomalies when the tracked locations indicate that one or more of the plurality of user devices has violated one or more the predetermined user mobility rules.

18. The computer readable medium of claim 17, wherein the instructions further cause the processor to associate the plurality of user devices with the user through determining that one or more of the plurality of user devices has logged into the network with a login associated with the user.

19. The computer readable medium of claim 17, wherein the instructions further cause the processor to associate the plurality of user devices with the user through clustering the plurality of user devices based on mobility cross entropy.

20. The computer readable medium of claim 17, wherein the instructions further cause the processor to track locations for the plurality of user devices by applying density based location tag partitioning to the location information.