Extrapolating trends in trust scores

• US 10,055,466 B2
• Filed: 05/08/2017
• Issued: 08/21/2018
• Est. Priority Date: 02/29/2016
• Status: Active Grant

• Current Assignee: www.TrustScience.com Inc.
• Original Assignee: www.TrustScience.com Inc.
• Inventors: Trudel, Chris, Mawji, Ashif
• Primary Examiner(s): Potratz, Daniel B
• Application Number:
  US15/589,841
• Publication Number:
  US 20170249315A1
• Time in Patent Office: 470 Days
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 21/316 by observing the pattern of computer usage, e.g. typical user behaviour
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/018 Certifying business or products
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 63/105 Multiple levels of security
• CPC Class Codes: H04L 63/126 the source of the received data
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

Systems and methods are described herein for extrapolating trends in trust scores. A trust score may reflect the trustworthiness, reputation, membership, status, and/or influence of the entity in a particular community or in relation to another entity. An entity'"'"'s trust score may be calculated based on data from a variety of data sources, and this data may be updated periodically as data is updated and new data becomes available. However, it may be difficult to update a trust score for an entity due to a scarcity of information. The trust score for such entities may be updated based on trends observed for the updated trust scores of other entities over a similar period of time. In this manner, trust scores may be updated for entities for which updated data is not available.

Claims

1. A method, comprising:

receiving, by a device of a computing network, the device comprising a processor, a request from a remote device of the computing network for a trust score for a first entity that reflects a first degree of trustworthiness of the first entity, the request comprising information identifying the first entity;

based on the receiving the request, retrieving by the device, an existing trust score for the first entity from a first database of the computing network; and

determining, by the device, that the existing trust score is outdated, and based on the determining that the existing trust score is outdated;

retrieving, by the device from the first database or a second database of the computing network, trust scores for a second entity determined over a period of time that extends to a more recent point in time relative to a past point in time at which the existing trust score was determined, wherein the trust scores for the second entity reflect a second degree of trustworthiness of the second entity;

determining, by the device, trend information associated with the second entity based on the trust scores, wherein the trend information reflects a degree of change in the trust scores determined for the second entity over the period of time; and

determining, by the device, an updated trust score for the first entity that reflects the first degree of trustworthiness of the first entity based on the existing trust score and the trend information.

2. The method of claim 1, wherein the trend information comprises slope data that reflects an average amount of increase or decrease in the trust scores over the period of time.

3. The method of claim 1, further comprising:

selecting, by the device, the second entity based on the second entity being determined to be related to the first entity based on at least one network path that connects the first entity and the second entity in the computing network.

4. The method of claim 1, further comprising:

selecting, by the device, the second entity based on the second entity being determined to be related to the first entity based on a connection between the first entity and the second entity by a path in the computing network having a threshold number of links.

5. The method of claim 1, wherein the request further comprises activity information identifying an activity to be performed by the first entity, and wherein the method further comprises:

selecting, by the device, the second entity based on a determination that the second entity previously performed the activity.

6. The method of claim 1, wherein the request further comprises attribute information identifying an attribute of the first entity, and wherein the method further comprises:

selecting, by the device, the second entity based on a determination that the second entity is associated with the attribute.

7. The method of claim 1, wherein the determining that the existing trust score is outdated is based on a difference between the past point in time and a current point in time at which the request is received being greater than a threshold difference.

8. The method of claim 1, wherein the existing trust score was determined based on a plurality of component trust scores respectively associated with different types of components, and wherein the determining that the existing trust score is outdated is based on a first type of component of the different types of components having an outdated component trust score.

9. The method of claim 8, wherein the trust scores for the second entity correspond to second component trust scores for the first type of component as determined for the second entity over the period of time.

10. The method of claim 9, wherein the trend information reflects a percentage increase or decrease in the second component trust scores for the first type of component as determined for the second entity over the period of time.

11. The method of claim 10, wherein the updated trust score reflects an increase or decrease to the outdated component trust score based on the percentage increase or decrease in the second component trust scores for the first type of component.

12. The method of claim 1, wherein the existing trust score was determined based on a plurality of component trust scores respectively associated with different types of components selected from the group consisting of:

a network connectivity component, a data verification component, a transaction history component, a search engine mining component, a credit score component, a court data component, a ratings/feedback data component, and a group/demographics component.

13. The method of claim 1, wherein the first degree of trustworthiness of the first entity is in relation to a third entity and wherein the request further comprising information identifying the third entity.

14. A first device of a computing network, comprising:

a processor, and

a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising;

receiving a request from a second device of the computing network for a trust score for a first entity of the computing network that reflects a first degree of trustworthiness of the first entity, the request comprising information identifying the first entity; and

based on the receiving the request, retrieving an existing trust score for the first entity from a database of the computing network; and

determining an updated trust score for the first entity that reflects the first degree of trustworthiness of the first entity based on a determination that the existing trust score is inaccurate, comprising;

determining trend information associated with a second entity of the computing network, wherein the trend information reflects a degree of change in trust scores determined for the second entity over a period of time that extends to a more recent point in time relative to a past point in time at which the existing trust score was determined, wherein the trust scores for the second entity reflect a second degree of trustworthiness of the second entity; and

determining the updated trust score based on the existing trust score and the trend information.

15. The device of claim 14, wherein the trend information comprises slope data that reflects an average amount of increase or decrease in the trust scores over the period of time.

16. The device of claim 14, wherein the determining the updated trust score further comprising:

selecting the second entity based on the second entity being determined to be related to the first entity based on a connection between the first entity and the second entity by a path in the computing network having a threshold number of links.

17. The device of claim 14, wherein the request further comprises activity information identifying an activity to be performed by the first entity, and wherein the determining the updated trust score further comprises:

selecting the second entity based on a determination that the second entity previously performed the activity.

18. A non-transitory machine-readable storage medium, comprising executable instructions that, when executed by a processor of a first device of a computing network, facilitate performance of operations, comprising:

receiving from a second device of the computing network, a request for a trust score for a first entity of the computing network that reflects a degree of trustworthiness of the first entity, the request comprising information identifying the first entity;

based on the receiving the request, retrieving an existing trust score for the first entity from a database of the computing network; and

determining an updated trust score for the first entity that reflects the degree of trustworthiness of the first entity based on a determination that the existing trust score is outdated, comprising;

determining trend information associated with a second entities of the computing network, wherein the trend information reflects a degree of change in trust scores determined for the second entities over a period of time that extends to a more recent point in time relative to a past point in time at which the existing trust score was determined, wherein the trust scores for the second entities respectively reflect degrees of trustworthiness of the second entities; and

determining the updated trust score based on the existing trust score and the trend information.

19. The non-transitory machine-readable storage medium of claim 18, wherein the trend information comprises slope data that reflects an average amount of increase or decrease in the trust scores over the period of time.

20. The non-transitory machine-readable storage medium of claim 18, wherein the operations further comprise:

selecting the second entity based on the second entity being determined to be related to the first entity based on a connection between the first entity and the second entity by a path in the computing network having a threshold number of links.