Method and apparatus for risk management

• US 20010027389A1
• Filed: 05/14/2001
• Published: 10/04/2001
• Est. Priority Date: 12/03/1999
• Status: Active Grant

• Current Assignee: Digital Sandbox, Inc. (Fishtech Group LLC)
• Original Assignee: Digital Sandbox, Inc. (Fishtech Group LLC)
• Inventors: Ware, Bryan, Beverina, Anthony
• Granted Patent: US 7,130,779 B2
• Time in Patent Office: Days
• US Class Current: 703/22
• CPC Class Codes: G06Q 20/203 Inventory monitoring
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G06Q 50/26 Government or public services business processes related to the transportation industry G06Q50/40

Abstract

An integrated risk management tool includes a persistent object database to store information about actors (individuals and/or groups), physical surroundings, historical events and other information. The risk management tool also includes a decision support system that uses data objects from the database and advanced decision theory techniques, such as Bayesian Networks, to infer the relative risk of an undesirable event. As part of the relative risk calculation, the tool uses a simulation and gaming environment in which artificially intelligent actors interact with the environment to determine susceptibility to the undesired event. Preferred embodiments of the tool also include an open “plug-in” architecture that allows the tool to interface with existing consequence calculators. The tool also provides facilities for presenting data in a user-friendly manner as well as report generation facilities.

Claims

1. An apparatus for assessing a risk of a terrorist attack comprising:

a memory;

an input device;

a display device; and

a processor connected to the memory, the input device and the display device, the processor being configured to perform the steps of;

inputting information about a site of potential terrorist attack from a user;

constructing a model of the site based on the information input from the user;

accepting a designation from the user of a weapon and delivery point at the site;

determitting an accessability of the site to the weapon/delivery point by determining a threat vector which is mostly likely the threat vector by which the weapon will be delivered and the likelihood of a successful delivery based on the model;

determining a probability that a terrorist attack will occur; and

calculating a relative risk based at least partially on the accessibility and probability.

2. The apparatus of

claim 1

, wherein the relative risk is further based on a consequence calculation.

3. The apparatus of

claim 2

, wherein the consequence calculations is performed by outputting data including model data to a consequence calculator plug-in and accepting consequence data from the plug-in.

4. The apparatus of

claim 1

, wherein the processor is further configured to perform the step of preparing a report including the probability, accessability and relative risk.

5. The apparatus of

claim 1

, wherein the processor is furter configured to perform the step of displaying a three dimensional representation of the most likely threat vector to the user.

6. The apparatus of

claim 1

, wherein the relative risk is calculated using a Bavesian network.

7. A method for assessing a risk of a terrorist attack comprising the steps of:

inputting information about a site of a potential terrorist attack from a user;

constructing a model of the site based on the input from the user;

accepting a designation from the user of a weapon and delivery point at the site;

determining an accessability of the site to the weapon/delivery point by determining a threat vector which is mostly likely the threat vector by which the weapon will be delivered and the likelihood of a successful delivery based on the model;

determining a probability that a terrorist attack will occur; and

calculating a relative risk based at least partially on the accessibility and probability.

8. The method of

claim 7

, wherein the relative risk is further based on a consequence calculation.

9. The method of

claim 8

, wherein the consequence calculations is performed by outputting data including model data to a consequence calculator plug-in and accepting consequence data from the plug-in.

10. The method of

claim 7

, wherein the processor is firther configured to perform the step of preparing a report including the probability, accessability and relative risk.

11. The method of

claim 7

, wherein the processor is further configured to perform the step of displaying a three dimensional representation of the most likely threat vector to the user.

12. The method of

claim 7

, wherein the relative risk is calculated using a Bayesian network.

13. A method of assessing risk comprising the steps of:

calculating a probability that an event will occur;

calculating a vulnerability to the event; and

calculating a relative risk based on the probability and vulnerability;

wherein the calculating steps are performed using an artificial intelligence network.

14. The method of

claim 13

, wherein the artificial intelligence network is a Bayesian network.

15. The method of

claim 13

, wherein the vulnerability is based upon a susceptability to the event and a consequence of the event.

16. The method of

claim 15

, wherein the susceptability is based upon an accessability which is determined from a model of a physical environment.

17. The method of

claim 13

, wherein the risk is a risk of a terrorist attack.

18. The method of

claim 13

, wherein the risk is a risk of an infrastructure attack.

19. The method of

claim 13

, wherein the risk is a risk of an information theft.

20. The method of

claim 13

, wherein the risk is financial loss.

21. The method of

claim 13

, wherein the risk is insurance loss.

22. The method of

claim 13

, wherein the risk is environmental hazard.

23. The method of

claim 13

, wherein the risk is risk of loss or damage to on-orbit satellite systems and constellations.

24. The method of

claim 13

, wherein the risk is associated with air travel.

25. The method of

claim 13

, wherein the risk is associated with highway travel.

26. The method of

claim 13

, wherein the risk is associated with manned and unmanned space travel.

27. The method of

claim 13

, wherein the risk is associated with military action.

28. The method of

claim 13

, wherein the risk is injury to a person.

29. The method of

claim 13

, wherein the risk is crime committed on a person.

30. The method of

claim 13

, wherein the risk is a risk to home security.

31. The method of

claim 13

, wherein the risk is a risk to building security.

32. The method of

claim 13

, wherein the risk is program and project risk management.

33. An apparatus for assessing risk comprising:

a database for storing information including information about at least one actor, physical surroundings, and expert observations;

a simulation and gaming environment in communication with the database for determining a threat vector and a likelihood that the threat will succeed;

a plug-in interface in communication with the database and connectable to a consequence calculator for outputting information from the database to the consequence calculator and inputting information concerining a consequence of an undesirable event; and

a decision support system in communication with the database for calculating a relative risk based on probability and vulnerability determined from information in the database and information from the simulation and gaming environment and the plug-in interface.

34. The apparatus of

claim 33

, further comprising a report generator for assembling a report concerning the relative risk.

35. The apparatus of

claim 34

, further comprising a theater information management system for sharing database information with remote terminals or computers.

36. The apparatus of

claim 33

, wherein the database is an object oriented database.

37. The apparatus of

claim 36

, wherein objects in the database are persistent objects.

38. The apparatus of

claim 33

, wherein the information in the database further includes historical information.

39. The apparatus of

claim 33

, further comprising an editor for editing information in the database.

40. The apparatus of

claim 33

, wherein the risk is a risk of terrorist attack.

41. The apparatus of

claim 33

, wherein the decision support system employs a Bayesian network.