Method and system for identifying users and detecting fraud by use of the internet

• US 8,862,514 B2
• Filed: 10/09/2008
• Issued: 10/14/2014
• Est. Priority Date: 03/02/2004
• Status: Expired due to Term

• Current Assignee: The 41st Parameter, Inc. (Experian plc)
• Original Assignee: The 41st Parameter, Inc. (Experian plc)
• Inventors: Eisen, Ori
• Primary Examiner(s): Coppola, Jacob C.
• Application Number:
  US12/248,867
• Publication Number:
  US 20090037213A1
• Time in Patent Office: 2,196 Days
• Field of Search: 705/73, 705/64, 705/44
• US Class Current: 705/44
• CPC Class Codes: G06F 21/73 by creating or determining hardware identification, e.g. serial numbers
• CPC Class Codes: G06Q 20/04 Payment circuits
• CPC Class Codes: G06Q 20/40 Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
• CPC Class Codes: G06Q 20/4016 involving fraud or risk level assessment in transaction processing
• CPC Class Codes: G06Q 30/0185 Product, service or business identity fraud

Abstract

A method and system for detecting and preventing Internet fraud in online transactions by utilizing and analyzing a number of parameters to uniquely identify a computer user and potential fraudulent transaction through predictive modeling. The method and system uses a delta of time between the clock of the computer used by the actual fraudulent use and the potentially fraudulent user and the clock of the server computer in conjunction with personal information and/or non-personal information, preferably the Browser ID.

Claims

1. A fingerprinting method to identify a user computer from other computers for an online transaction with an electronic commerce business comprising the steps of:

creating, with aid of a processor, a first computer identifier in the course of a first online transaction with the electronic commerce business, and a second computer identifier in the course of a second online transaction with the electronic commerce business, wherein the first computer identifier identifies the user computer, wherein each computer identifier includes a delta of time parameter defined during the course of the online transaction by a time difference measured between a first clock measurement equal to a user computer local time and a second clock measurement equal to an electronic commerce business local time over a selected time interval;

flagging the first computer identifier in response to determining the first online transaction may be a fraudulent transaction;

comparing, with aid of the processor, the first computer identifier and the second computer identifier;

determining, with aid of the processor, that a measured difference between the delta of time parameter of the first computer identifier and the delta of time parameter of the second computer identifier falls within a selected range; and

indicating, to the electronic commerce business, that the user computer was used in the first online transaction and the second online transaction, based at least on the determination that the measured difference falls within the selected range.

2. The method as recited in claim 1, wherein the first clock measurement and the second clock measurement are each a measured using a JavaScript.

4. The method as recited in claim 1, wherein each computer identifier further includes additional parameters including personal identification information.

5. The method as recited in claim 4, wherein the personal identification information includes consumer identification information.

6. The method as recited in claim 5, wherein the consumer identification information includes at least one of the following:

consumer name, address, billing information, shipping information, telephone number and e-mail address.

7. The method as recited in claim 1, wherein each computer identifier further includes at least one non-personal identification parameter.

8. The method as recited in claim 7, wherein the non-personal identification parameter is computer identification information.

9. The method as recited in claim 8, wherein the computer identification information includes an Internet parameter.

10. The method as recited in claim 9, wherein the Internet parameter is a CGI parameter.

11. The method as recited in claim 10, wherein the CGI parameter includes a Browser ID.

12. The method as recited in claim 1, wherein each computer identifier includes relevant time zone information in which the user computer is physically located.

13. The method as recited in claim 1, wherein the delta of time parameter is stored as a range of time.

3. A non-transitory computer readable medium having instructions stored thereon that, when executed by a processor, cause the processor to perform a method to identify a user computer from other computers for an online transaction with an electronic commerce business, the method comprising:

creating a first computer identifier in the course of a first online transaction with the electronic commerce business, and a second computer identifier in the course of a second online transaction with the electronic commerce business, wherein the first computer identifier identifies the user computer, wherein each computer identifier includes a delta of time parameter defined during the course of the online transaction by a time difference measured between a first clock measurement equal to a user computer local time and a second clock measurement equal to an electronic commerce business local time over a selected time interval;

flagging the first computer identifier in response to determining the first online transaction may be a fraudulent transaction;

comparing the first computer identifier and the second computer identifier;

determining that a measured difference between the delta of time parameter of the first computer identifier and the delta of time parameter of the second computer identifier falls within a selected range; and

indicating, to the electronic commerce business, that the user computer was used in the first online transaction and the second online transaction, based at least on the determination that the measured difference falls within the selected range.