IP Library › Granted Patent US 10,193,897

Granted Patent B2

US 10,193,897 · App. 15/589,703 · Granted Jan 29, 2019

Identity and trustworthiness verification using online and offline components

Inventors: Stephen Kirkham (San Francisco, CA); Michael Lewis (San Francisco, CA)

Assignee: Airbnb, Inc.

H04L63/126 G06F21/31 G06F21/316

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Quick Facts

Patent No.: US 10,193,897
App. No.: 15/589,703
Granted: Jan 29, 2019
Kind: B2

External Links

USPTO Patent Center↗ Full Patent PDF↗

Abstract

Methods and systems for verifying the identity and trustworthiness of a user of an online system are disclosed. In one embodiment, the method comprises receiving online and offline identity information for a user and comparing them to a user profile information provided by the user. Furthermore, the user's online activity in a third party online system and the user's offline activity are received. Based on the online activity and the offline activity a trustworthiness score may be calculated.

Claims (58)

1. A computer implemented method, comprising:

receiving, from a user, by a computer, information about a first online identity of the user of a first-party online system, the first online identity including a first name and a last name of the user;

receiving from the user, credentials for an account of the user in a third-party online system;

sending a request to the third party online system for information about a second online identity of the user, the request including the credentials, the third party online system different than the first-party online system;

receiving, from the third-party online system, information about activities performed by the user in the third-party online system;

determining an online trustworthiness score based at least on the information about the activities performed by the user in the third-party online system;

sending a request to one or more databases for information associated with first name and the last name of the user;

receiving, from the one or more databases, offline information about an the user;

determining an offline trustworthiness score based on the offline information; and

determining a trustworthiness score based on the online trustworthiness score and the offline trustworthiness score; and

responsive to determining that the trustworthiness score of the user is below a threshold value, exiting the user out from creating a user account in the first-party online system.

2. The computer implemented method of claim 1 , wherein the online trustworthiness score is further based on a date the account of the user in the third-party online system was created.

3. The computer implemented method of claim 1 , wherein the online trustworthiness score is further based on a date the account of the user in the third-party online system was updated.

4. The computer implemented method of claim 1 , wherein the online trustworthiness score is further based on a browsing behavior of the user.

5. The computer implemented method of claim 1 , wherein the trustworthiness score is based on a trained machine learning algorithm.

6. The computer implemented method of claim 1 , wherein the one or more databases includes at least one of a sex offender database, a criminal records database, and a credit bureau database.

7. The computer implemented method of claim 1 , further comprising:

receiving, from other users of the first-party online system, one or more comments associated with the user; and

wherein the offline trustworthiness score is further based on the one or more comments associated with the user.

8. The computer implemented method of claim 7 , wherein the offline trustworthiness score is further based on a recency of the one or more comments associated with the user.

9. A system comprising:

a hardware processor; and

a computer readable medium configured to store instructions, the instructions when executed by a processor cause the processor to:

receive, from a user, by a computer, information about a first online identity of the user of a first-party online system, the first online identity including a first name and a last name of the user;

receive from the user, credentials for an account of the user in a third-party online system;

send a request to the third party online system for information about a second online identity of the user, the request including the credentials, the third party online system different than the first-party online system;

receive, from the third-party online system, information about activities performed by the user in the third-party online system;

determine an online trustworthiness score based at least on the information about the activities performed by the user in the third-party online system;

send a request to one or more databases for information associated with first name and the last name of the user;

receive, from the one or more databases, offline information about an the user;

determine an offline trustworthiness score based on the offline information; and

determine a trustworthiness score based on the online trustworthiness score and the offline trustworthiness score; and

responsive to determining that the trustworthiness score of the user is below a threshold value, exit the user out from creating a user account in the first-party online system.

10. The system of claim 9 , wherein the online trustworthiness score is further based on a date the account of the user in the third-party online system was created.

11. The system of claim 9 , wherein the online trustworthiness score is further based on a date the account of the user in the third-party online system was updated.

12. The system of claim 9 , wherein the online trustworthiness score is further based on a browsing behavior of the user.

13. The system of claim 9 , wherein the trustworthiness score is based on a trained machine learning algorithm.

14. The system of claim 9 , wherein the one or more databases includes at least one of a sex offender database, a criminal records database, and a credit bureau database.

15. The system of claim 9 , wherein the instructions when executed by the processor further cause the processor to:

receive, from other users of the first-party online system, one or more comments associated with the user; and

wherein the offline trustworthiness score is further based on the one or more comments associated with the user.

16. The system of claim 15 , wherein the offline trustworthiness score is further based on a recency of the one or more comments associated with the user.

17. A non-transitory computer readable storage medium configured to store instructions, the instructions when executed by a processor, cause the processor to: