TRUST CALCULATOR FOR PEER-TO-PEER TRANSACTIONS

• US 20160283994A1
• Filed: 03/25/2015
• Published: 09/29/2016
• Est. Priority Date: 03/25/2015
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Mathai, Shiju, Edgington, Jeffrey L., Kwan, Hung T.
• Application Number:
  US14/668,164
• Publication Number:
  US 20160283994A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: G06Q 30/018 Certifying business or products
• CPC Class Codes: G06Q 30/0609 Buyer or seller confidence or verification
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083

Abstract

A system, method and program product that evaluates trustworthiness of nodes participating in peer-to-peer transactions. A system is disclosed that includes: an input process for receiving a resource request from a consumer node; an identification analyzer that collects metadata associated with the consumer node; a transaction analyzer that extracts contextual data associated with the resource request; a matching engine that matches the consumer node with a set of provider nodes; and a contextual trust scoring engine that calculates a trust score for each of the consumer node and the set of provider nodes, wherein the trust score is based on the request, the metadata, and the contextual data.

Claims

1. A trust system that evaluates trustworthiness of nodes participating in peer-to-peer transactions, comprising:

an input process for receiving a resource request from a consumer node;

an identification analyzer that collects metadata associated with the consumer node;

a transaction analyzer that extracts contextual data associated with the resource request;

a matching engine that matches the consumer node with a set of provider nodes; and

a contextual trust scoring engine that calculates a trust score for each of the consumer node and the set of provider nodes, wherein the trust score is based on the request, the metadata, and the contextual data.

2. The trust system of claim 1, wherein the metadata includes:

credential verification, relationship analysis, social network data analysis, and public record search results.

3. The trust system of claim 1, wherein the contextual data includes:

a location analysis, an environment analysis, and a time analysis.

4. The trust system of claim 1, wherein the matching engine utilizes the trust score to rank the set of provider nodes.

5. The trust system of claim 1, wherein the resource request comprises a request for transportation services, and the contextual data includes a neighborhood analysis.

6. The trust system of claim 1, wherein the identity analyzer collects and stores metadata associated with registered provider nodes.

7. The trust system of claim 6, further comprising a crawler that periodically updates the metadata associated with registered provider nodes.

8. A computer program product stored on a computer readable storage medium, which when executed by a computing system, evaluates trustworthiness of nodes participating in peer-to-peer transactions, comprising:

program code for receiving a resource request from a consumer node;

program code that collects metadata associated with the consumer node;

program code that extracts contextual data associated with the resource request;

program code that matches the consumer node with a set of provider nodes; and

program code that calculates a trust score for each of the consumer node and the set of provider nodes, wherein the trust score is based on the request, the metadata, and the contextual data.

9. The program product of claim 8, wherein the metadata includes at least one of:

credential verification, relationship analysis, social network data analysis, and public record search results.

10. The program product of claim 8, wherein the contextual data includes at least one of:

a location analysis, an environment analysis, and a time analysis.

11. The program product of claim 8, wherein matching consumer node with a set of provider nodes utilizes the trust score to rank the set of provider nodes.

12. The program product of claim 8, wherein the resource request comprises a request for transportation services, and the contextual data includes a neighborhood analysis.

13. The program product of claim 8, further comprising program code that collects and stores metadata associated with registered provider nodes.

14. The program product of claim 13, further comprising program code that periodically updates the metadata associated with registered provider nodes.

15. A method for evaluating trustworthiness of nodes participating in a peer-to-peer environment, comprising:

receiving a resource request from a consumer node;

collecting metadata associated with the consumer node;

extracting contextual data associated with the resource request;

matching the consumer node with a set of provider nodes; and

calculating a trust score for each of the consumer node and the set of provider nodes, wherein the trust score is based on the request, the metadata, and the contextual data.

16. The method of claim 15, wherein the metadata includes at least one of:

credential verification, relationship analysis, social network data analysis, and public record search results.

17. The method of claim 15, wherein the contextual data includes at least one of:

a location analysis, an environment analysis, and a time analysis.

18. The method of claim 15, wherein matching consumer node with a set of provider nodes utilizes the trust score to rank the set of provider nodes.

19. The method of claim 15, wherein the resource request comprises a request for transportation services, and the contextual data includes a neighborhood analysis.

20. The method of claim 15, further comprising program code that collects and stores metadata associated with registered provider nodes.