IP Library Granted Patent US 11,539,645
Granted Patent B2
US 11,539,645 · App. 17/320,271 · Granted Dec 27, 2022

Cloud-based spam detection

Inventors: Ann E. Skudlark (San Ramon, CA); Lien K. Tran (Seattle, WA); Yu Jin (Madison, NJ)
Assignee: AT&T Intellectual Property I, L.P.
H04L51/212H04L63/1408H04W4/14G06F9/45533G06F9/45558G06F2009/45595H04L51/58
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Quick Facts
Patent No.
US 11,539,645
App. No.
17/320,271
Granted
Dec 27, 2022
Kind
B2
Abstract

A cloud based mobile internet protocol messaging spam defense. Short message service (SMS) messages are analyzed by a cloud based virtual machine to determine if should be considered potentially unwanted messages (e.g., spam). The cloud based virtual machine uses a user specific algorithm for determining if a message should be considered to be a potentially unwanted message. Messages that are determined to be potentially unwanted messages trigger a notification to be sent to a user device associated with the virtual machine. The notification requests confirmation from the user that the potentially unwanted message is an unwanted message. The user's response to a request for confirmation is then used to update an unwanted message database associated with the user and the user device.

Claims (39)

1. A method, comprising:

identifying, by a server, a user associated with messages;

identifying, by the server, a virtual machine that is associated with the user;

identifying, by the server, a user-specific algorithm selected by the user

requesting a cloud-based spam detection service that is provided by the virtual

machine, wherein the virtual machine identifies a potential spam message by

analyzing the messages using the user-specific algorithm; and

updating, by the server, the user-specific algorithm based on a confirmation that the potential spam message is spam.

2. The method of claim 1 , further comprising determining a messaging account associated with the user.

3. The method of claim 1 , further comprising determining a messaging account associated with the messages.

4. The method of claim 1 , further comprising determining a messaging account associated with the cloud-based spam detection service.

5. The method of claim 1 , further comprising determining a sender associated with the potential spam message.

6. A system, comprising:

a hardware processor; and

a memory device, the memory device storing instructions, the instructions when executed causing the hardware processor to perform operations, the operations comprising:

identifying a recipient associated with messages;

identifying a virtual machine that is associated with the recipient;

identifying a user-specific algorithm selected by the recipient for a cloud-based spam detection service that is provided by the virtual machine;

identifying a potential spam message by analyzing the messages using the user-specific algorithm selected by the recipient for the cloud-based spam detection service; and

updating the user-specific algorithm based on a confirmation that the potential spam message is spam.

7. The system of claim 6 , wherein the operations further comprise determining a sender associated with the potential spam message.

8. The system of claim 6 , wherein the operations further comprise determining a messaging account associated with the recipient.

9. The system of claim 6 , wherein the operations further comprise determining a messaging account associated with the messages.

10. The system of claim 6 , wherein the operations further comprise determining a messaging account associated with the cloud-based spam detection service.

11. A non-transitory memory device storing instructions that when executed cause a hardware processor to perform operations, the operations comprising:

identifying a recipient associated with messages;

identifying a virtual machine that is associated with the recipient;

identifying a user-specific algorithm selected by the recipient for a cloud-based spam detection service that is provided by the virtual machine;

identifying a potential spam message by analyzing the messages using the user-specific algorithm; and

updating the user-specific algorithm based on a confirmation that the potential spam message is spam.

12. The non-transitory memory device of claim 11 , wherein the operations further comprise determining a sender associated with the potential spam message.

13. The non-transitory memory device of claim 11 , wherein the operations further comprise determining a messaging account associated with the recipient.

14. The non-transitory memory device of claim 11 , wherein the operations further comprise determining a messaging account associated with the messages.

15. The non-transitory memory device of claim 11 , wherein the operations further comprise determining a messaging account associated with the cloud-based spam detection service.

16. The non-transitory memory device of claim 11 , wherein the operations further comprise requesting a credential from a user device associated with the recipient.

17. The non-transitory memory device of claim 16 , wherein the operations further comprise logging into a messaging account using the credential, wherein the messages are associated with the messaging account.

18. The non-transitory memory device of claim 17 , wherein the operations further comprise retrieving the messages from the messaging account prior to a delivery of the messages to the user device.

19. The non-transitory memory device of claim 16 , wherein the identifying of the virtual machine is based on the credential.

20. The non-transitory memory device of claim 11 , wherein the virtual machine is executed by a server to provide the cloud-based spam detection service.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 25, 2021
From: SKUDLARK, ANN E.; TRAN, LIEN K.; JIN, YU
To: AT&T INTELLECTUAL PROPERTY I, L.P.
Reel/Frame 056346/0807 →
Continuity (4)
Continuation 16901056 · Jun 15, 2020
Continuation 15910289 · Mar 2, 2018
Continuation 14543364 · Nov 17, 2014
Related Publication 20210273898A1 · Sep 2, 2021