IP Library › Granted Patent US 12,301,608
Granted Patent B1
US 12,301,608 · App. 17/677,237 · Granted May 13, 2025

Identification of one or more services for a user's network-connected smart device using a smart device fingerprint of the network-connected smart device

Inventors: Michael D. Melnick (Brighton, NY); Christopher R. McCooey (Pleasant Hill, CA); David L. Knudsen (Saint Helena, CA)
Assignee: EVERYTHING SET INC.
H04L63/1433H04L63/1425H04W8/18H04L63/08
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 12,301,608
App. No.
17/677,237
Granted
May 13, 2025
Kind
B1
Abstract

One or more services are identified for a user's network-connected smart device by generating a smart device fingerprint for the network-connected smart device, electronically communicating the smart device fingerprint for the network-connected smart device to a processor, and analyzing the data in the smart device fingerprint for the network-connected smart device in the processor and identifying one or more services based on the data in the smart device fingerprint for the network-connected smart device. The smart device fingerprint including at least device metadata of the network-connected smart device, a vulnerability profile of the network-connected smart device, and anomaly and/or behavior metadata of the network-connected smart device.

Claims (42)

1. A method for identifying one or more services for a user's network-connected smart device, wherein the user's network-connected smart device is associated with application software that executes on a mobile device of the user, the method comprising:

(a) generating a smart device fingerprint for the network-connected smart device, the smart device fingerprint including at least the following data:

(i) device metadata of the network-connected smart device,

(ii) vulnerability profile of the network-connected smart device, and

(iii) one or more of:

(A) anomaly metadata of the network-connected smart device, and

(B) behavior metadata of the network-connected smart device;

(b) electronically communicating the smart device fingerprint for the network-connected smart device to a processor via an electronic network;

(c) analyzing the data in the smart device fingerprint for the network-connected smart device in the processor and identifying one or more services based on the data in the smart device fingerprint for the network-connected smart device, wherein the one or more services that are identified based on the data in the smart device fingerprint were not previously identified; and

(d) the processor electronically communicating the one or more identified services to the application software executing on the mobile device of the user, thereby delivering the one or more services to the mobile device of the user,

wherein the user's network-connected smart device and the mobile device of the user are distinct and separate devices, and

wherein the device metadata of the network-connected device is distinct from the vulnerability profile of the network-connected device, and

wherein the anomaly metadata of the network-connected device is distinct from the behavior metadata of the network-connected device.

2. The method of claim 1 , wherein one of the services is a recommendation based on the vulnerability profile to apply a specific update to the user's network-connected smart device.

3. The method of claim 1 , wherein one of the services is the delivery of targeted content associated with the user's network-connected smart device, wherein the targeted content is selected based on the device metadata.

4. The method of claim 1 , wherein one of the services is a notification based on the anomaly or behavior data indicating that the user's network-connected smart device is communicating with one or more suspect network addresses.

5. The method of claim 1 , wherein one of the services is a notification that the user should upgrade or replace the user's network-connected smart device, wherein the notification is based one on or more elements of the smart fingerprint data.

6. The method of claim 1 , wherein the device metadata includes at least an operating system of the network-connected smart device.

7. The method of claim 1 , wherein the device metadata includes at least a device make of the network-connected smart device.

8. The method of claim 1 , wherein the device metadata includes at least a device make and model of the network-connected smart device.

9. The method of claim 1 wherein one of the services is to provide IP blocking service for the user's network-connected smart device.

10. A method for identifying one or more services for a user's network-connected smart device, the method comprising:

(a) generating a smart device fingerprint for the network-connected smart device, the smart device fingerprint including at least the following data:

(i) device metadata of the network-connected smart device,

(ii) vulnerability profile of the network-connected smart device, and

(iii) behavior metadata of network-connected smart device;

(b) electronically communicating the smart device fingerprint for the network-connected smart device to a processor via an electronic network; and

(c) analyzing the data in the smart device fingerprint for the network-connected smart device in the processor and identifying one or more services based on the data in the smart device fingerprint for the network-connected smart device, wherein the one or more services that are identified based on the data in the smart device fingerprint were not previously identified, and

wherein the device metadata of the network-connected device is distinct from the vulnerability profile of the network-connected device.

11. The method of claim 10 , wherein the user's network-connected smart device is associated with application software that executes on a mobile device of the user, the method further comprising:

(d) the processor electronically communicating the one or more identified services to the application software executing on the mobile device of the user, thereby delivering the one or more services to the mobile device of the user,

wherein the user's network-connected smart device and the mobile device of the user are distinct and separate devices.

12. The method of claim 10 , wherein one of the services is a recommendation based on the vulnerability profile to apply a specific update to the user's network-connected smart device.

13. The method of claim 10 , wherein one of the services is the delivery of targeted content associated with the user's network-connected smart device, wherein the targeted content is selected based on the device metadata.

14. The method of claim 10 , wherein the smart device fingerprint further includes anomaly metadata of the network-connected smart device, and

wherein one of the services is a notification based on the anomaly metadata indicating that the user's network-connected smart device is communicating with one or more suspect network addresses,

wherein the anomaly metadata of the network-connected device is distinct from the behavior metadata of the network-connected device.

15. The method of claim 10 , wherein one of the services is a notification that the user should upgrade or replace the user's network-connected smart device, wherein the notification is based one on or more elements of the smart fingerprint data.

16. The method of claim 10 , wherein the device metadata includes at least an operating system of the network-connected smart device.

17. The method of claim 10 , wherein the device metadata includes at least a device make of the network-connected smart device.

18. The method of claim 10 , wherein the device metadata includes at least a device make and model of the network-connected smart device.

19. The method of claim 10 wherein one of the services is to provide IP blocking service for the user's network-connected smart device.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 23, 2022
From: MELNICK, MICHAEL D.; MCCOOEY, CHRISTOPHER R.; KNUDSEN, DAVID L.
To: EVERYTHING SET INC.
Reel/Frame 059076/0315 →
References Cited (43)
US 9349103B2 · Eberhardt, III et al. · 2016 [cited by applicant]
US 9537876B2 · Kelekar · 2017 [cited by applicant]
US 9621517B2 · Martini · 2017 [cited by applicant]
US 9838292B2 · Polychronis · 2017 [cited by applicant]
US 9984365B2 · Desai et al. · 2018 [cited by applicant]
US 10063585B2 · Salajegheh et al. · 2018 [cited by applicant]
US 10142122B1 · Hill et al. · 2018 [cited by applicant]
US 10454950B1 · Aziz · 2019 [cited by applicant]
US 10587633B2 · Muddu et al. · 2020 [cited by applicant]
US 11057409B1 · Bisht et al. · 2021 [cited by applicant]
US 11184386B1 · Schroeder · 2021 [cited by examiner]
US 11658863B1 · Salinas et al. · 2023 [cited by applicant]
US 20090265784A1 · Waizumi et al. · 2009 [cited by applicant]
US 20100285820A1 · Jozwiak · 2010 [cited by examiner]
US 20110239274A1 · Heffez · 2011 [cited by examiner]
US 20140066015A1 · Aissi · 2014 [cited by examiner]
US 20140181972A1 · Karta et al. · 2014 [cited by applicant]
US 20150033340A1 · Giokas · 2015 [cited by applicant]
US 20150163121A1 · Mahaffey et al. · 2015 [cited by applicant]
US 20160006753A1 · McDaid et al. · 2016 [cited by applicant]
US 20160112374A1 · Branca · 2016 [cited by applicant]
US 20160232358A1 · Grieco et al. · 2016 [cited by applicant]
US 20180139179A1 · Ettema · 2018 [cited by examiner]
US 20190114404A1 · Nowak · 2019 [cited by examiner]
US 20190306182A1 · Fry et al. · 2019 [cited by applicant]
US 20190380037A1 · Lifshitz et al. · 2019 [cited by applicant]
US 20200044927A1 · Apostolopoulos et al. · 2020 [cited by applicant]
US 20200366689A1 · Lotia · 2020 [cited by examiner]
US 20200396211A1 · Dobbins · 2020 [cited by examiner]
US 20210006583A1 · Ryabenkiy et al. · 2021 [cited by applicant]
US 20210306341A1 · Tiwari et al. · 2021 [cited by applicant]
US 20230188540A1 · Valluri et al. · 2023 [cited by applicant]
Bayesian Hierarchical Models in Ecology, Chapter4 Bayesian Machinery, downloaded from:<https://bookdown.org/steve_midway/BHME/Ch3.html>, download date: Jan. 31, 2022, initial posting date: unknown, 12 pages. [cited by applicant]
D.4. dumpcap: Capturing with “dumpcap” for viewing with Wireshark, Appendix D. Related command line tools, downloaded from webpage: <https://www.wireshark.org/docs/wsug_html_chunked/AppToolsdumpcap.html>, download date:… [cited by applicant]
Fing DeveRecog API—Fing Device Recognition Cloud API, Fing Limited, Nov. 4, 2019, 10 pages. [cited by applicant]
Sivanathan et al. “Can We Classify an IoT Device using TCP Port Scan?” downloaded from: <https://www2.ee.unsw.edu.au/˜hhabibi/pubs/conf/18iciafs-1.pdf> 2018 IEEE International Conference on Information and Automation fo… [cited by applicant]
Tshark(1) Manual Page, downloaded from: <https://www.wireshark.org/docs/man-pages/tshark.html>, download date: Feb. 1, 2022, initial posting date: unknown, 37 pages. [cited by applicant]
WAGO 852 Industrial Managed Switch Series Code Execution/Hardcoded Credentials, downloaded from web page: <https://vulners.com/packetstorm/PACKETSTORM:153278> download date: Feb. 3, 2022, initial posting date: unknown, … [cited by applicant]
Wikipedia entry for “Man-in-the-middle attack.” page last edited on Sep. 5, 2021, 7 pages. [cited by applicant]
Wikipedia entry for “Prior Probability,” page last edited on Mar. 13, 2021, 8 pages. [cited by applicant]
Notice of Allowance issued Apr. 15, 2024 in U.S. Appl. No. 17/677,235. [cited by applicant]
Li et al., “Crowdsourcing based large-scale network anomaly detection,” IEEE, pp. 1-6 (2018). [cited by applicant]
Sanchez et al., “A Survey on Device Behavior Fingerprinting: Data Sources, Techniques, Application Scenarios, adn Datasets,” IEEE Communications Surveys & Tutorials, vol. 23, No. 2, pp. 1048-1077 (2021). [cited by applicant]