IP Library Granted Patent US 9,356,947
Granted Patent B2
US 9,356,947 · App. 14/680,918 · Granted May 31, 2016

Methods and systems for analyzing data related to possible online fraud

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Quick Facts
Patent No.
US 9,356,947
App. No.
14/680,918
Granted
May 31, 2016
Kind
B2
Abstract

Various embodiments of the invention provide methods, systems and software for analyzing data. In particular embodiments, for example, a set of data about a web site may be analyzed to determine whether the web site is likely to be illegitimate (e.g., to be involved in a fraudulent scheme, such as a phishing scheme, the sale of gray market goods, etc.). In an exemplary embodiment, a set of data may be divided into a plurality of components (each of which, in some cases, may be considered a separate data set). Merely by way of example, a set of data may comprise data gathered from a plurality of data sources, and/or each component may comprise data gathered from one of the plurality of data source. As another example, a set of data may comprise a document with a plurality of sections, and each component may comprise one of the plurality of sections. Those skilled in the art will appreciate that the analysis of another component may comprise certain tests and/or evaluations, and that the analysis of another component may comprise different tests and/or evaluations. In other cases, the analysis of each component may comprise similar tests and/or evaluations. The variety of tests and/or evaluations generally will be implementation specific.

Claims (55)

1. A method, comprising:

periodically collecting, with a computer, from a plurality of different sources, a set of data related to a web site, wherein the set of data comprises a web page on the web site;

dividing, with the computer, the set of data into a plurality of components, the plurality of components including at least an Internet Protocol (“IP”) address associated with the web site and a body field comprising text;

analyzing at least two of the components, wherein analyzing the at least two of the plurality of components comprises:

analyzing the text of the body field to identify at least one of a pre-defined blacklisted term and a brand name;

identifying a domain of the web site;

identifying an Internet Protocol (“IP”) block assigned to the domain; and

comparing the IP address of the web site with the IP block assigned to the domain;

assigning at least one score to one or more of the analyzed components; and

categorizing the web site as a possibly fraudulent web site, based at least in part on the at least one score.

2. The method of claim 1 , wherein upon categorizing the web site as a possibly fraudulent web site, the method further comprising identifying additional terms in the text of the body field as new blacklisted terms, and adding at least one of the new blacklisted terms as a pre-defined blacklisted term.

3. The method of claim 1 , wherein the set of data further comprises at least one of a zone file, an Internet chat session and a newsgroup.

4. The method of claim 1 , wherein the set of data further comprises an email message.

5. The method of claim 4 , wherein the plurality of components further comprises:

a header portion of the email message;

a body portion of the email message; and

a uniform resource locator (“URL”) incorporated within the body portion of the email message, the URL referring to the web site.

6. The method of claim 1 , wherein the set of data further comprises a set of data about a server hosting the web site.

7. The method of claim 6 , wherein collecting the set of data about the server hosting the web site comprises interrogating the web site.

8. A computer system, comprising a hardware processor and a set of instructions executable by the hardware processor, the set of instructions comprising:

instructions for periodically collecting, from a plurality of different sources, a set of data related to a web site, wherein the set of data comprises a web page on the web site;

instructions for dividing the set of data into a plurality of components, the plurality of components comprising an Internet Protocol (“IP”) address associated with the web site and a body field comprising text;

instructions for analyzing at least two of the plurality of components, comprising:

instructions for analyzing the text of the body field to identify at least one of a pre-defined blacklisted term and a brand name;

instructions for identifying a domain of the web site;

instructions for identifying an Internet Protocol (“IP”) block assigned to the domain; and

instructions for comparing the IP address of the web site with the IP block assigned to the domain;

instructions for assigning at least one score to one or more of the analyzed components; and

instructions for categorizing the web site as a possibly fraudulent web site, based at least in part on the at least one score.

9. The computer system of claim 8 , wherein the instructions for analyzing at least two of the plurality of components are configured to analyze at least one of a zone file, an Internet chat session and a newsgroup.

10. The computer system of claim 8 , wherein the instructions for analyzing at least two of the plurality of components are configured to analyze an email message.

11. The computer system of claim 10 , wherein the plurality of components further comprises:

a header portion of the email message;

a body portion of the email message; and

a uniform resource locator (“URL”) incorporated within the body portion of the email message, the URL referring to the web site.

12. The computer system of claim 8 , wherein the instructions for analyzing at least two of the plurality of components are configured to analyze set of data about a server hosting the web site.

13. The computer system of claim 12 , wherein collecting the set of data about the server hosting the web site comprises interrogating the web site.

14. The computer system of claim 8 , further comprising instructions for, upon categorizing the web site as a possibly fraudulent web site, identifying additional terms in the text of the body field as new blacklisted terms, and adding at least one of the new blacklisted terms as a pre-defined blacklisted term.

15. A software program embodied on a non-transitory computer readable medium, the software program comprising a set of instructions executable by one or more computers, the set of instructions comprising:

instructions for periodically collecting, from a plurality of different sources, a set of data related to a web site, wherein the set of data comprises a web page on the web site;

instructions for dividing the set of data into a plurality of components, wherein the plurality of components comprises an Internet Protocol (“IP”) address associated with the web site and a body field comprising text;

instructions for analyzing at least two of the plurality of components, comprising:

instructions for analyzing the text of the body field to identify at least one of a pre-defined blacklisted term and a brand name;

instructions for identifying a domain of the web site;

instructions for identifying an Internet Protocol (“IP”) block assigned to the domain; and

instructions for comparing the IP address of the web site with the IP block assigned to the domain;

instructions for assigning at least one score to at least some of the analyzed components; and

instructions for categorizing the web site as a possibly fraudulent web site, based at least in part on the at least one score.

16. The software program of claim 15 , wherein the instructions for analyzing at least two of the plurality of components are configured to analyze an email message.

17. The software program of claim 16 , wherein the plurality of components further comprises:

a header portion of the email message;

a body portion of the email message; and

a uniform resource locator (“URL”) incorporated within the body portion of the email message, the URL referring to the web site.

18. The software program of claim 15 , further comprising instructions for, upon categorizing the web site as a possibly fraudulent web site, identifying additional terms in the text of the body field as new blacklisted terms, and adding at least one of the new blacklisted terms as a pre-defined blacklisted term.

19. The software program of claim 15 , wherein the instructions for analyzing at least two of the plurality of components are configured to analyze at least one of a zone file, an Internet chat session and a newsgroup.

Assignments (9)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 10, 2020
From: CAMELOT UK BIDCO LIMITED
To: OPSEC ONLINE LIMITED
Reel/Frame 052070/0544 →
SECURITY INTEREST Recorded Nov 1, 2019
From: CAMELOT UK BIDCO LIMITED
To: BANK OF AMERICA, N.A.
Reel/Frame 050906/0284 →
SECURITY INTEREST Recorded Nov 1, 2019
From: CAMELOT UK BIDCO LIMITED
To: WILMINGTON TRUST, N.A. AS COLLATERAL AGENT
Reel/Frame 050906/0553 →
RELEASE OF SECURITY INTEREST Recorded Nov 1, 2019
From: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH, AS COLLATERAL AGENT
To: CAMELOT UK BIDCO LIMITED
Reel/Frame 050911/0796 →
SECURITY INTEREST Recorded Oct 3, 2016
From: CAMELOT UK BIDCO LIMITED
To: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH, AS COLLATERAL AGENT
Reel/Frame 040205/0156 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 3, 2016
From: THOMSON REUTERS GLOBAL RESOURCES
To: CAMELOT UK BIDCO LIMITED
Reel/Frame 040206/0448 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 9, 2016
From: SHRAIM, IHAB; SHULL, MARK
To: EMARKMONITOR, INC.
Reel/Frame 039681/0458 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 9, 2016
From: MARKMONITOR INC.
To: THOMSON REUTERS GLOBAL RESOURCES
Reel/Frame 039980/0458 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 9, 2016
From: EMARKMONITOR, INC.
To: MARKMONITOR INC.
Reel/Frame 039984/0519 →