RISK ASSESSMENT USING SOCIAL NETWORKING DATA

• US 20190327261A1
• Filed: 05/06/2019
• Published: 10/24/2019
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Socure, Inc.
• Original Assignee: Socure, Inc.
• Inventors: MADHU, Sunil, PALLOTTI, Giacomo, ROMANO, Edward J., CHAVEZ, Alexander K.
• Granted Patent: US 10,542,032 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 21/577 Assessing vulnerabilities and evaluating computer system security
• CPC Class Codes: G06Q 20/4016 involving fraud or risk level assessment in transaction processing
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: G06Q 50/265 Personal security, identity or safety
• CPC Class Codes: H04L 51/52 for supporting social networking services
• CPC Class Codes: H04L 63/12 Applying verification of the received information cryptographic mechanisms or cryptographic arrangements for data integrity or data verification H04L9/32
• CPC Class Codes: H04L 63/1408 by monitoring network traffic monitoring network traffic per se H04L43/00
• CPC Class Codes: H04L 63/1433 Vulnerability analysis
• CPC Class Codes: H04L 63/1483 service impersonation, e.g. phishing, pharming or web spoofing detection of rogue wireless access points H04W12/12
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04W 12/12 Detection or prevention of fraud
• CPC Class Codes: H04W 12/67 Risk-dependent, e.g. selecting a security level depending on risk profiles
• CPC Class Codes: H04W 4/21 for social networking applications

Abstract

Tools, strategies, and techniques are provided for evaluating the identities of different entities to protect individual consumers, business enterprises, and other organizations from identity theft and fraud. Risks associated with various entities can be analyzed and assessed based on analysis of social network data, professional network data, or other networking connections, among other data sources. In various embodiments, the risk assessment may include calculating an authenticity score based on the collected network data.

Claims

1. (canceled)

2. A computer-implemented method for calculating a risk score for a user account, the method comprising:

(a) calculating, by an electronic processor of a computer system, a user score by comparing profile data of a first user account to at least one reference profile model associated with at least one online network, the at least one reference profile model including a fake profile;

(b) calculating, by the processor, a connections score in response to detecting at least one social connection, within the at least one online network, between the first user account and at least a second user account;

(c) calculating, via the processor, a risk score for the first user account based on the calculated user score and the calculated connections score; and

(d) generating, by the processor, an alert based on the risk score.

3. The method of claim 2, wherein the profile data comprises at least one of:

user contact information, friend data, birth data, network data, geolocation data, image data, video data, or timeline activity associated with at least one user account.

4. The method of claim 2, wherein calculating the user score further comprises processing at least one activity feed of at least the first user account by calculating a frequency of posting.

5. The method of claim 2, wherein calculating the user score further comprises checking an identity of one or more user accounts making a post to distinguish between a post by the first user account and a post by at least a second user account connected to the first user account.

6. The method of claim 2, wherein calculating the user score further comprises processing at least one attribute of at least one application installed on at least the first user account.

7. The method of claim 2, wherein calculating the user score further comprises comparing at least a portion of the profile data of the first user to multiple reference profile models associated with multiple networks.

8. The method of claim 2, wherein calculating the connections score comprises processing data associated with connections formed between the first user account and at least one account associated with a friend, family member, follower, owner, or peer of the first user account.

9. The method of claim 2, further comprising communicating at least one alert to a user account in association with at least one of the calculated scores.

10. The method of claim 2, wherein calculating the risk score includes combining data associated with at least one transaction involving the first user account or the second user account.

11. The method of claim 2, further comprising communicating at least one of the calculated scores to an enterprise using an application program interface.

12. The method of claim 2, further comprising calculating a risk score for at least the second user account.

13. The method of claim 2, further comprising generating, via the processor, a dashboard, wherein the dashboard is configured to display at least one of:

a) a number of transactions performed by one or more user accounts;

b) at least one risk score associated with a plurality of user accounts;

c) at least one risk score in association with a social network, a professional network, an online network, a domain, a demographic characteristic, a psychographic characteristic, or a combination thereof; and

d) a graphical representation associated with at least one of the user score, the connections score, the risk score, or a combination of multiple scores.

14. A computer-implemented system for calculating a risk score for a user account, the system comprising:

a) at least one processor, an operating system configured to perform executable instructions, and a memory;

b) a computer program including instructions executable by the at least one processor to create an application comprising;

i) a software module configured to calculate a user score by comparing at least a portion of profile data of a first user account to at least one reference profile model associated with at least one online network, the at least one reference profile model including a fake profile;

ii) a software module configured to calculate a connections score in response to detecting at least one social connection, within the at least one online network, between the first user account and at least a second user account;

iii) a software module configured to calculate a risk score for the first user account based on the calculated user score and the calculated connections score; and

iv) a software module configured to cause display of an alert based on the risk score.

15. The computer-implemented system of claim 14, wherein the profile data comprises at least one of:

user contact information, friend data, birth data, network data, geolocation data, image data, video data, or timeline activity associated with at least one user account.

16. The computer-implemented system of claim 14, wherein the software module configured to calculate the user score is further configured to calculate the user score by processing at least one activity feed of at least the first user account by calculating a frequency of posting.

17. The computer-implemented system of claim 14, the application further comprising a software module configured to generate a dashboard, the dashboard configured to display at least one of:

a) a number of transactions performed by one or more user accounts;

b) at least one risk score associated with a plurality of user accounts;

c) at least one risk score in association with a social network, a professional network, an online network, a domain, a demographic characteristic, a psychographic characteristic, or a combination thereof; and

d) a graphical representation associated with at least one of the user score, the connections score, the risk score, or a combination of multiple scores.

18. A non-transitory computer-readable storage medium storing computer-executable instructions to:

calculate a user score by comparing profile data of the first user account to at least one reference profile model associated with at least one online network, the at least one reference profile model including a fake profile;

calculate a connections score in response to detecting at least one social connection, within the at least one online network, between the first user account and at least a second user account;

calculate a risk score for at least the first user account based on the calculated user score and the calculated connections score;

revising the at least one reference profile model based on a comparison of the calculated risk score to an average score range for at least one cluster of other entities; and

generate an alert based on the risk score.

19. The non-transitory computer-readable storage medium of claim 18, wherein the profile data comprises at least one of:

user contact information, friend data, birth data, network data, geolocation data, image data, video data, or timeline activity associated with at least one user account.

20. The non-transitory computer-readable storage medium of claim 18, wherein the instructions to calculate the user score further include instructions to process at least one activity feed of at least the first user account by calculating a frequency of posting.

21. The non-transitory computer-readable storage medium of claim 18, further storing computer-executable instructions to generate a dashboard, the dashboard configured to display at least one of:

a) a number of transactions performed by one or more user accounts;

b) at least one risk score associated with a plurality of user accounts;

c) at least one risk score in association with a social network, a professional network, an online network, a domain, a demographic characteristic, a psychographic characteristic, or a combination thereof; and

d) a graphical representation associated with at least one of the user score, the connections score, the risk score, or a combination of multiple scores.