IP Library › Granted Patent US 12,299,704
Granted Patent B2
US 12,299,704 · App. 18/362,680 · Granted May 13, 2025

Systems and methods for anonymous behavioral-based records identification

Inventors: Seth Haberman (New York, NY); Claudio Marcus (Andover, NH)
Assignee: Free Wheel Media, Inc.
G06Q30/0201
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,299,704
App. No.
18/362,680
Granted
May 13, 2025
Kind
B2
Abstract

Methods, systems, and computer-readable media for identifying users, records, and/or devices using anonymous source data records associated with consumer activity are described. In general, the consumer activity may relate to consumer interactions with devices and/or content or data through devices. The source data records may be structured, such as associating the source data records with a sequential timeline. Behavioral markers may be generated by the matching system and associated with the source data records. Each behavioral marker may be analyzed across all of the source data records to determine the effectiveness of the behavioral marker to identify unique source data records. One or more of the behavioral markers may be used to generate a behavioral fingerprint. A behavioral fingerprint may be used to identify unique records, devices, and/or users, including identification based on different sets of source data records.

Claims (46)

1. A method, comprising:

receiving, from one or more computing devices, data comprising information associated with user interactions with the one or more computing devices;

generating, based on the user interactions, one or more behavioral markers;

generating, based at least in part on the one or more behavioral markers, one or more behavioral fingerprints comprising information related to at least one computing device of the one or more computing devices; and

matching, based on the one or more behavioral fingerprints, at least a portion of the data to the at least one computing device that is indicative of consumer activity at the at least one computing device.

2. The method of claim 1 , further comprising associating the data with a timeline of the user interactions over a time duration, wherein the generating the one or more behavioral markers is further based on the timeline of the user interactions over the time duration.

3. The method of claim 1 , further comprising determining an effectiveness of the one or more behavioral markers, wherein the generating the one or more behavioral fingerprints is further based at least in part on the effectiveness of the one or more behavioral markers.

4. The method of claim 1 , further comprising causing, based on the one or more behavioral fingerprints, output of identifying information comprising information unique to the at least one computing device.

5. The method of claim 1 , further comprising:

receiving, from a computing device associated with a matching system, a request for the one or more behavioral fingerprints; and

sending, based on the request and to the computing device associated with the matching system, the one or more behavioral fingerprints.

6. The method of claim 1 , further comprising:

receiving, from a computing device associated with a matching system, a request for the one or more behavioral markers; and

sending, based on the request and to the computing device associated with the matching system, the one or more behavioral markers.

7. The method of claim 1 , wherein the one or more behavioral fingerprints are generated based at least in part on an aggregation of the one or more behavioral markers.

8. The method of claim 1 , wherein the information associated with the user interactions comprises anonymous source data records associated with consumer activity.

9. An apparatus, comprising:

one or more processors; and

memory storing instructions that, when executed by the one or more processors, cause the apparatus to:

receive, from one or more computing devices, data comprising information associated with user interactions with the one or more computing devices;

generate, based on the user interactions, one or more behavioral markers;

generate, based at least in part on the one or more behavioral markers, one or more behavioral fingerprints comprising information related to at least one computing device of the one or more computing devices; and

match, based on the one or more behavioral fingerprints, at least a portion of the data to the at least one computing device that is indicative of consumer activity at the at least one computing device.

10. The apparatus of claim 9 , wherein the instructions, when executed by the one or more processors, further cause the apparatus to associate the data with a timeline of the user interactions over a time duration, wherein the generating the one or more behavioral markers is further based on the timeline of the user interactions over the time duration.

11. The apparatus of claim 9 , wherein the instructions, when executed by the one or more processors, further cause the apparatus to determine an effectiveness of the one or more behavioral markers, wherein the generating the one or more behavioral fingerprints is further based at least in part on the effectiveness of the one or more behavioral markers.

12. The apparatus of claim 9 , wherein the instructions, when executed by the one or more processors, further cause the apparatus to cause, based on the one or more behavioral fingerprints, output of identifying information comprising information unique to the at least one computing device.

13. The apparatus of claim 9 , wherein the instructions, when executed by the one or more processors, further cause the apparatus to:

receive, from a computing device associated with a matching system, a request for the one or more behavioral fingerprints; and

send, based on the request and to the computing device associated with the matching system, the one or more behavioral fingerprints.

14. The apparatus of claim 9 , wherein the instructions, when executed by the one or more processors, further cause the apparatus to:

receive, from a computing device associated with a matching system, a request for the one or more behavioral markers; and

send, based on the request and to the computing device associated with the matching system, the one or more behavioral markers.

15. A non-transitory computer-readable medium storing instructions that, when executed, cause:

receiving, from one or more computing devices, data comprising information associated with user interactions with the one or more computing devices;

generating, based on the user interactions, one or more behavioral markers;

generating, based at least in part on the one or more behavioral markers, one or more behavioral fingerprints comprising information related to at least one computing device of the one or more computing devices; and

matching, based on the one or more behavioral fingerprints, at least a portion of the data to the at least one computing device that is indicative of consumer activity at the at least one computing device.

16. The non-transitory computer-readable medium of claim 15 , wherein the instructions, when executed, further cause associating the data with a timeline of the user interactions over a time duration, wherein the generating the one or more behavioral markers is further based on the timeline of the user interactions over the time duration.

17. The non-transitory computer-readable medium of claim 15 , wherein the instructions, when executed, further cause determining an effectiveness of the one or more behavioral markers, wherein the generating the one or more behavioral fingerprints is further based at least in part on the effectiveness of the one or more behavioral markers.

18. The non-transitory computer-readable medium of claim 15 , wherein the instructions, when executed, further cause causing, based on the one or more behavioral fingerprints, output of identifying information comprising information unique to the at least one computing device.

19. The non-transitory computer-readable medium of claim 15 , wherein the instructions, when executed, further cause:

receiving, from a computing device associated with a matching system, a request for the one or more behavioral fingerprints; and

sending, based on the request and to the computing device associated with the matching system, the one or more behavioral fingerprints.

20. The non-transitory computer-readable medium of claim 15 , wherein the instructions, when executed, further cause:

receiving, from a computing device associated with a matching system, a request for the one or more behavioral markers; and

sending, based on the request and to the computing device associated with the matching system, the one or more behavioral markers.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 14, 2023
From: HABERMAN, SETH; MARCUS, CLAUDIO
To: VISIBLE WORLD, INC.
Reel/Frame 064583/0010 →
MERGER Recorded Aug 14, 2023
From: VISIBLE WORLD, LLC
To: FREEWHEEL MEDIA, INC.
Reel/Frame 064583/0183 →
CHANGE OF NAME Recorded Aug 14, 2023
From: VISIBLE WORLD, INC.
To: VISIBLE WORLD, LLC
Reel/Frame 064586/0915 →
Continuity (5)
Continuation 17512254 · Oct 27, 2021
Continuation 16058822 · Aug 8, 2018
Continuation 14643921 · Mar 10, 2015
Provisional Application 61950393 · Mar 10, 2014
Related Publication 20240029085A1 · Jan 25, 2024
References Cited (37)
US 7099946B2 · Lennon et al. · 2006 [cited by applicant]
US 7930252B2 · Bender et al. · 2011 [cited by applicant]
US 8027864B2 · Gilbert · 2011 [cited by applicant]
US 8949890B2 · Evans et al. · 2015 [cited by applicant]
US 9015163B1 · Skolicki et al. · 2015 [cited by applicant]
US 9514293B1 · Moritz · 2016 [cited by examiner]
US 10074096B2 · Haberman et al. · 2018 [cited by applicant]
US 10269029B1 · Evans et al. · 2019 [cited by applicant]
US 11195188B2 · Haberman et al. · 2021 [cited by applicant]
US 11798012B2 · Haberman · 2023 [cited by examiner]
US 20020010864A1 · Safa · 2002 [cited by applicant]
US 20070106606A1 · Pankratz et al. · 2007 [cited by applicant]
US 20070206606A1 · Coleman et al. · 2007 [cited by applicant]
US 20070214037A1 · Shubert et al. · 2007 [cited by applicant]
US 20070279187A1 · Hekmatpour et al. · 2007 [cited by applicant]
US 20080092168A1 · Logan et al. · 2008 [cited by applicant]
US 20100332319A1 · Etchegoyen · 2010 [cited by applicant]
US 20110113007A1 · Buckley · 2011 [cited by applicant]
US 20110137975A1 · Das et al. · 2011 [cited by applicant]
US 20110221771A1 · Cramer et al. · 2011 [cited by applicant]
US 20120023547A1 · Maxson et al. · 2012 [cited by applicant]
US 20120323694A1 · Lita et al. · 2012 [cited by applicant]
US 20130055300A1 · Hanina · 2013 [cited by applicant]
US 20130102283A1 · Lau et al. · 2013 [cited by applicant]
US 20130124315A1 · Doughty et al. · 2013 [cited by applicant]
US 20130133052A1 · Davis et al. · 2013 [cited by applicant]
US 20130191887A1 · Davis · 2013 [cited by examiner]
US 20130197968A1 · Davis et al. · 2013 [cited by applicant]
US 20130346148A1 · Roth et al. · 2013 [cited by applicant]
US 20140244351A1 · Symons · 2014 [cited by applicant]
US 20140244641A1 · Patterson · 2014 [cited by applicant]
US 20160142379A1 · Tawakol et al. · 2016 [cited by applicant]
JP 2004512583 · 2004 [cited by applicant]
WO 2013151905A2 · 2013 [cited by applicant]
Giura et al., “Is it really you? User identification via adaptive behavior fingerprinting”, In Proceedings of the 4th ACM conference on Data and application security and privacy, Association for Computing Machinery, 201… [cited by applicant]
US Patent Application filed on Oct. 27, 2021, entitled “Systems And Methods For Anonymous Behavioral-Based Records Identification”, U.S. Appl. No. 17/512,130. [cited by applicant]
US Patent Application filed on Oct. 27, 2021, entitled “Systems And Methods For Anonymous Behavioral-Based Records Identification”, U.S. Appl. No. 17/512,254. [cited by applicant]