Identification breach detection

• US 9,032,531 B1
• Filed: 03/15/2013
• Issued: 05/12/2015
• Est. Priority Date: 06/28/2012
• Status: Expired due to Fees

• Current Assignee: MiddleGate, Inc.
• Original Assignee: MiddleGate, Inc.
• Inventors: Stull, Edward L., Scorvo, Sean Kristofer
• Primary Examiner(s): Zee, Edward
• Application Number:
  US13/844,750
• Time in Patent Office: 788 Days
• Field of Search: 726/22, 726/23, 726/24, 726/25
• US Class Current: 726/25
• CPC Class Codes: G06F 21/55 Detecting local intrusion or implementing counter-measures
• CPC Class Codes: G06F 21/6254 by anonymising data, e.g. decorrelating personal data from the owner's identification
• 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

Abstract

Systems and methods are disclosed for detecting data breaches and, more specifically, disclosed herein are systems and methods for detecting data breaches and preventing fraud, including healthcare insurance fraud, using both a computer association component (Interpretation model) and a self sensitizing/self de-sensitizing component (SS/SDS model) using a breach observation line (BOL).

Claims

1. A data breach detection and fraud prevention system comprising:

(a) an Interpretation model to facilitate probability interpretation, risk assignment, and match correlation;

(b) a self-sensitizing/self de-sensitizing model that executes virtual patterning methods where the virtual patterning methods allow for forensic analysis of breach events;

(c) a correlator and reporter module comprising a processor, in which said Interpretation model and said self-sensitizing/self de-sensitizing model are executed and correlated, and in which multiple domains are monitored for breach events by measuring a degree of match of predetermined data elements of electronic records against records present in at least one monitored domain, and in which virtual breach concern bars indicating the significance of findings for each monitored domain are generated, and in which said breach concern bars are connected with a virtual line to create a virtual breach observation line; and

(d) wherein said correlator and reporter module detects data breaches using multiple domain breach event correlations graphically illustrated as said virtual breach observation line connecting said breach concern bars that indicate the significance of findings for each monitored domain.

2. The system of claim 1, wherein said system is used to prevent fraud.

3. The system of claim 1, wherein said system is used to prevent healthcare insurance fraud.

4. The system of claim 1, said correlator and reporter module monitoring at least two domains selected from the group of domains comprising:

(a) a hospital/clinic domain;

(b) a hackersphere domain;

(c) a CMS data center domain;

(d) an ID Monitoring Service (IDMS) domain; and

(e) an insurance domain.

5. The system of claim 1, wherein said correlator and reporter module monitors multiple domains for breach events by measuring a degree of match of predetermined data elements of a patient'"'"'s electronic medical records against records present in at least one monitored domain.

6. A method for data breach detection and fraud prevention system, said method comprising the steps of:

(a) facilitating probability interpretation, risk assignment, and match correlation using an Interpretation model;

(b) executing, on a processor, virtual patterning methods where the virtual patterning methods allow for forensic analysis of breach events using a self-sensitizing/self de-sensitizing model;

(c) executing and correlating, on a processor, said Interpretation model and said self-sensitizing/self de-sensitizing model using a correlator and reporter module;

(d) monitoring multiple domains using said correlator and reporter module for breach events by measuring a degree of match of predetermined data elements of electronic records against records present in at least one monitored domain;

(e) generating virtual breach concern bars indicating the significance of findings for each monitored domain;

(f) connecting said breach concern bars with a virtual line to create a virtual breach observation line; and

(g) detecting data breaches using multiple domain breach event correlations using said correlator and reporter module.

7. The method of claim 6, said method preventing fraud.

8. The method of claim 6, said method preventing healthcare insurance fraud by providing early detection of Patient Information breach.

9. The method of claim 6, said step of monitoring multiple domains further comprising monitoring at least two domains selected from the group of domains comprising:

(a) a hospital/clinic domain;

(b) a hackersphere domain;

(c) a CMS data center domain;

(d) an ID Monitoring Service (IDMS) domain; and

(e) an insurance domain.

10. The method of claim 6, said step of monitoring multiple domains further comprising the step of monitoring multiple domains for breach events by measuring a degree of match of predetermined data elements of a patient'"'"'s electronic medical records against said records present in at least one monitored domain.

11. The method of claim 6, using said virtual breach observation line, graphically illustrating a correlation of various domains.

12. The method of claim 6, said step of connecting said breach concern bars with a virtual line to create a virtual breach observation line further comprising the

step of connecting said breach concern bars with said virtual line at normalized mid-points of said breach concern bars to create said virtual breach observation line.

13. A method for data breach detection and fraud prevention system, said method comprising the steps of:

(a) facilitating probability interpretation, risk assignment, and match correlation using an Interpretation model;

(b) executing, on a processor, virtual patterning methods where the virtual patterning methods allow for forensic analysis of breach events using a self-sensitizing/self de-sensitizing model;

(c) executing and correlating, on a processor, said Interpretation model and said self-sensitizing/self de-sensitizing model using a correlator and reporter module;

(d) monitoring multiple domains for breach events by measuring a degree of match of predetermined data elements of a patient'"'"'s electronic medical records against records present in at least one monitored domain;

(e) using at least one breach observation line, graphically illustrating a correlation of various domains;

(f) generating virtual breach concern bars indicating the significance of findings for each monitored domain;

(g) connecting said breach concern bars with at least one virtual line to create said at least one breach observation line; and

(h) said method preventing healthcare insurance fraud by providing early detection of Patient Information breach.

14. The method of claim 13, said step of monitoring multiple domains further comprising monitoring at least two domains selected from the group of domains comprising:

(a) a hospital/clinic domain;

(b) a hackersphere domain;

(c) a CMS data center domain;

(d) an ID Monitoring Service (IDMS) domain; and

(e) an insurance domain.

15. The method of claim 13, said step of connecting said breach concern bars with at least one virtual line to create said at least one breach observation line further comprising the

step of connecting said breach concern bars with said at least one virtual line at normalized mid-points of said breach concern bars to create said at least one breach observation line.