IP Library Granted Patent US 10,855,702
Granted Patent B2
US 10,855,702 · App. 16/432,791 · Granted Dec 1, 2020

Threat mitigation system and method

Inventors: Brian P. Murphy (Tampa, FL); Joe Partlow (Tampa, FL); Colin O'Connor (Tampa, FL); Jason Pfeiffer (Tampa, FL)
Assignee: ReliaQuest Holdings, LLC
H04L63/1416G06F8/65G06F21/53G06F21/55G06F21/554G06F21/56G06F21/561G06F21/562G06F21/566G06F21/568G06F21/577G06F30/20G06K9/6256G06N20/00H04L63/0227H04L63/0263H04L63/145H04L63/1425H04L63/1433H04L63/1441H04L63/164H04L63/20G06F2221/034G06F2221/2115
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Quick Facts
Patent No.
US 10,855,702
App. No.
16/432,791
Granted
Dec 1, 2020
Kind
B2
Abstract

A computer-implemented method, computer program product and computing system is provided that may be utilized in a threat mitigation system. The method may include displaying initial security-relevant information that includes analytical information. The method may also include allowing a third-party to manipulate the initial security-relevant information with automation information. The method may further include generating revised security-relevant information that includes the automation information.

Claims (75)

1. A computer-implemented method, executed on a computing device, comprising:

generating, via one or more security-relevant subsystems, initial security-relevant information, wherein the one or more security-relevant subsystems include one or more of a content delivery network system, a database activity monitoring system, a user behavior analytics system, a mobile device management system, an identity and access management system, and a domain name server system;

displaying the initial security-relevant information that includes analytical information;

allowing a third-party to manipulate the initial security-relevant information with automation information;

generating revised security-relevant information, resulting from the manipulated initial security-relevant information, that includes the automation information;

obtaining one or more security-relevant information sets from each of the one or more security-relevant subsystems;

defining an initial probabilistic model for accomplishing at least one defined task based on the one or more security-relevant information sets, the at least one defined task including a training routine for a specific attack of a computing platform, wherein defining the initial probabilistic model for accomplishing the at least one defined task includes generating a simulation of the specific attack;

identifying one or more commonalities amongst the one or more security-relevant information sets, via the initial probabilistic model, using artificial intelligence/machine learning; and

combining the one or more security-relevant information sets based on the one or more commonalities to form an aggregated security-relevant information set of the initial security-relevant information and the revised security-relevant information.

2. The computer-implemented method of claim 1 further comprising:

rendering the revised security-relevant information.

3. The computer-implemented method of claim 2 wherein rendering the revised security-relevant information includes:

rendering the revised security-relevant information within an interactive report.

4. The computer-implemented method of claim 1 wherein allowing a third-party to manipulate the initial security-relevant information with automation information includes:

allowing a third-party to select automation information to add to the initial security-relevant information to generate the revised security-relevant information.

5. The computer-implemented method of claim 4 wherein allowing a third-party to select the automation information to add to the initial security-relevant information to generate the revised security-relevant information includes:

allowing the third-party to choose a specific type of automation information from a plurality of automation information types.

6. The computer-implemented method of claim 1 wherein generating revised security-relevant information that includes the automation information includes:

combining the automation information and the initial security-relevant information to generate the revised security-relevant information.

7. The computer-implemented method of claim 1 wherein the analytical information includes one or more of:

investigative information; and

hunting information.

8. The computer-implemented method of claim 1 wherein the automation information includes one or more of:

automated information; and

orchestrated information.

9. A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising:

generating, via one or more security-relevant subsystems, initial security-relevant information, wherein the one or more security-relevant subsystems include one or more of a content delivery network system, a database activity monitoring system, a user behavior analytics system, a mobile device management system, an identity and access management system, and a domain name server system;

displaying the initial security-relevant information that includes analytical information;

allowing a third-party to manipulate the initial security-relevant information with automation information;

generating revised security-relevant information, resulting from the manipulated initial security-relevant information, that includes the automation information;

obtaining one or more security-relevant information sets from each of the one or more security-relevant subsystems;

defining an initial probabilistic model for accomplishing at least one defined task based on the one or more security-relevant information sets, the at least one defined task including a training routine for a specific attack of a computing platform, wherein defining the initial probabilistic model for accomplishing the at least one defined task includes generating a simulation of the specific attack;

identifying one or more commonalities amongst the one or more security-relevant information sets, via the initial probabilistic model, using artificial intelligence/machine learning; and

combining the one or more security-relevant information sets based on the one or more commonalities to form an aggregated security-relevant information set of the initial security-relevant information and the revised security-relevant information.

10. The computer program product of claim 9 further comprising:

rendering the revised security-relevant information.

11. The computer program product of claim 10 wherein rendering the revised security-relevant information includes:

rendering the revised security-relevant information within an interactive report.

12. The computer program product of claim 9 wherein allowing a third-party to manipulate the initial security-relevant information with automation information includes:

allowing a third-party to select automation information to add to the initial security-relevant information to generate the revised security-relevant information.

13. The computer program product of claim 12 wherein allowing a third-party to select the automation information to add to the initial security-relevant information to generate the revised security-relevant information includes:

allowing the third-party to choose a specific type of automation information from a plurality of automation information types.

14. The computer program product of claim 9 wherein generating revised security-relevant information that includes the automation information includes:

combining the automation information and the initial security-relevant information to generate the revised security-relevant information.

15. The computer program product of claim 9 wherein the analytical information includes one or more of:

investigative information; and

hunting information.

16. The computer program product of claim 9 wherein the automation information includes one or more of:

automated information; and

orchestrated information.

17. A computing system including a processor and memory configured to perform operations comprising:

generating, via one or more security-relevant subsystems, initial security-relevant information, wherein the one or more security-relevant subsystems include one or more of a content delivery network system, a database activity monitoring system, a user behavior analytics system, a mobile device management system, an identity and access management system, and a domain name server system;

displaying the initial security-relevant information that includes analytical information;

allowing a third-party to manipulate the initial security-relevant information with automation information;

generating revised security-relevant information, resulting from the manipulated initial security-relevant information, that includes the automation information;

obtaining one or more security-relevant information sets from each of the one or more security-relevant subsystems;

defining an initial probabilistic model for accomplishing at least one defined task based on the one or more security-relevant information sets, the at least one defined task including a training routine for a specific attack of a computing platform, wherein defining the initial probabilistic model for accomplishing the at least one defined task includes generating a simulation of the specific attack;

identifying one or more commonalities amongst the one or more security-relevant information sets, via the initial probabilistic model, using artificial intelligence/machine learning; and

combining the one or more security-relevant information sets based on the one or more commonalities to form an aggregated security-relevant information set of the initial security-relevant information and the revised security-relevant information.

18. The computing system of claim 17 further comprising:

rendering the revised security-relevant information.

19. The computing system of claim 16 wherein rendering the revised security-relevant information includes:

rendering the revised security-relevant information within an interactive report.

20. The computing system of claim 17 wherein allowing a third-party to manipulate the initial security-relevant information with automation information includes:

allowing a third-party to select automation information to add to the initial security-relevant information to generate the revised security-relevant information.

21. The computing system of claim 20 wherein allowing a third-party to select the automation information to add to the initial security-relevant information to generate the revised security-relevant information includes:

allowing the third-party to choose a specific type of automation information from a plurality of automation information types.

22. The computing system of claim 17 wherein generating revised security-relevant information that includes the automation information includes:

combining the automation information and the initial security-relevant information to generate the revised security-relevant information.

23. The computing system of claim 17 wherein the analytical information includes one or more of:

investigative information; and

hunting information.

24. The computing system of claim 17 wherein the automation information includes one or more of:

automated information; and

orchestrated information.

Assignments (4)
RELEASE OF SECURITY INTEREST Recorded May 1, 2024
From: SIXTH STREET SPECIALTY LENDING, INC.
To: RELIAQUEST HOLDINGS, LLC
Reel/Frame 067277/0607 →
SECURITY INTEREST Recorded Apr 30, 2024
From: RELIAQUEST HOLDINGS, LLC
To: GOLUB CAPITAL LLC, AS COLLATERAL AGENT
Reel/Frame 067274/0381 →
SECURITY INTEREST Recorded Oct 8, 2020
From: RELIAQUEST HOLDINGS, LLC
To: SIXTH STREET SPECIALTY LENDING, INC., AS COLLATERAL AGENT
Reel/Frame 054013/0548 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 7, 2020
From: MURPHY, BRIAN P.; PARTLOW, JOE; O'CONNOR, COLIN; PFEIFFER, JASON
To: RELIAQUEST HOLDINGS, LLC
Reel/Frame 052333/0915 →
Continuity (4)
Provisional Application 62681279 · Jun 6, 2018
Provisional Application 62737558 · Sep 27, 2018
Provisional Application 62817943 · Mar 13, 2019
Related Publication 20190377882A1 · Dec 12, 2019
Cited By (1)
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