Jason W Vaughn

US Patent:

20200257803, Aug 13, 2020

Filed:

Apr 27, 2020

Appl. No.:

16/858779

Inventors:

- Charlotte NC, US
Jason Dean Vaughn - Jacksonville FL, US
Allan Carlton Byers - Charlotte NC, US

Assignee:

BANK OF AMERICA CORPORATION - Charlotte NC

International Classification:

G06F 21/57
H04L 29/06
G06F 21/64

Abstract:

Embodiments of the present invention are directed to data integration and threat assessment for triggering analysis of connection oscillations in order to improve data and connection security. The invention leverages a security threat assessment engine and an analytics engine to gather and process data from a combination of internal and external data sources for a third party connection. The system continuously monitors and updates a generated threat level for a third party connection to determine changes or triggers indicating a potential security threat. In response to these determined changes or triggers, the system then responds to a detected security threat and minimizes damages resulting from data compromised by third party systems. Further, the system may extract and recover data from the third party systems and alter connection channels in order to further limit losses.

US Patent:

20200167481, May 28, 2020

Filed:

Jan 30, 2020

Appl. No.:

16/777505

Inventors:

- Charlotte NC, US
Robert James Gray - Southlake TX, US
Cory David Brunner - Stanley NC, US
Jason Dean Vaughn - Jacksonville FL, US
Ryan Joseph Argomaniz - Sachse TX, US

Assignee:

BANK OF AMERICA CORPORATION - Charlotte NC

International Classification:

G06F 21/57
H04L 29/06

Abstract:

A system for generating entity-specific security-related inquiries and determining a frequency for invoking the inquiries based on integration of external security-related data and internal security related data. Specifically, a security threat level is determined for an entity and the components which comprise the security threat are identified. The components signify areas of focus for generating the entity-specific security-related inquiries. In further embodiments of the invention analytics are implemented to logically analyze the external security-related data and internal security related data and the results of which further refine the generation of the entity-specific security-related inquiries and/or determination of the frequency for invoking the inquiries.

US Patent:

20200162502, May 21, 2020

Filed:

Jan 27, 2020

Appl. No.:

16/773726

Inventors:

- Charlotte NC, US
Jason Dean Vaughn - Jacksonville FL, US

Assignee:

BANK OF AMERICA CORPORATION - Charlotte NC

International Classification:

H04L 29/06

Abstract:

The invention utilizes a two-component system to detect third party security threats and drive improved security threat mitigation based on the detection. The first component of the system is a security threat assessment engine, which receives and/or identifies external data and internal data regarding third parties in order to determine information security threats posed by third parties. The second component of the system is an analytics engine, which may comprise a machine learning component which is configured to detect threat patterns and anomalies. In response to the detection of the threat patterns and anomalies the security threat assessment engine may be modified in order to more accurately determine security threats.

US Patent:

20200120129, Apr 16, 2020

Filed:

Dec 10, 2019

Appl. No.:

16/708805

Inventors:

- Charlotte NC, US
Jason Dean Vaughn - Jacksonville FL, US

Assignee:

Bank of America Corporation - Charlotte NC

International Classification:

H04L 29/06

Abstract:

The invention utilizes a two-component system to detect third party security threats and drive internal system processes based on the detection. The first component of the system is a threat level engine, which collects external and internal system data on a real-time basis to determine changes in conditions that may give rise to a security threat. Based on the external and internal data, the level engine may calculate a threat assessment level to determine the level of the threat. The second component of the system is a third party analytics engine, which may comprise a machine learning component which is configured to detect threat patterns and anomalies, which may in turn be used to trigger events or to drive internal system processes.

US Patent:

20190163914, May 30, 2019

Filed:

Nov 30, 2017

Appl. No.:

15/827034

Inventors:

- Charlotte CA, US
Robert James Gray - Southlake TX, US
Cory David Brunner - Stanley NC, US
Jason Dean Vaughn - Jacksonville FL, US
Ryan Joseph Argomaniz - Sachse TX, US

International Classification:

G06F 21/57
H04L 29/06

Abstract:

A system for generating entity-specific security-related inquiries and determining a frequency for invoking the inquiries based on integration of external security-related data and internal security related data. Specifically, a security threat level is determined for an entity and the components which comprise the security threat are identified. The components signify areas of focus for generating the entity-specific security-related inquiries. In further embodiments of the invention analytics are implemented to logically analyze the external security-related data and internal security related data and the results of which further refine the generation of the entity-specific security-related inquiries and/or determination of the frequency for invoking the inquiries.

US Patent:

20190163915, May 30, 2019

Filed:

Nov 30, 2017

Appl. No.:

15/827097

Inventors:

- Charlotte NC, US
Jason Dean Vaughn - Jacksonville FL, US
Mathew Allen Woodyard - Chicago IL, US
Allan Carlton Byers - Charlotte NC, US

International Classification:

G06F 21/57
H04L 29/06

Abstract:

The invention utilizes a two-component system to detect third party security threats and drive improved security threat mitigation based on the detection. The first component of the system is a security threat assessment engine, which receives and/or identifies external data and internal data regarding third parties in order to determine information security threats posed by third parties. The second component of the system is an analytics engine, which may comprise a machine learning component which is configured to detect threat patterns and anomalies. In response to the detection of the threat patterns and anomalies the security threat assessment engine may be modified in order to more accurately determine security threats.

US Patent:

20190163916, May 30, 2019

Filed:

Nov 30, 2017

Appl. No.:

15/827515

Inventors:

- Charlotte NC, US
Jason Dean Vaughn - Jacksonville FL, US
Allan Carlton Byers - Charlotte NC, US

International Classification:

G06F 21/57
G06F 21/64
H04L 29/06

Abstract:

Embodiments of the present invention are directed to data integration and threat assessment for triggering analysis of connection oscillations in order to improve data and connection security. The invention leverages a security threat assessment engine and an analytics engine to gather and process data from a combination of internal and external data sources for a third party connection. The system continuously monitors and updates a generated threat level for a third party connection to determine changes or triggers indicating a potential security threat. In response to these determined changes or triggers, the system then responds to a detected security threat and minimizes damages resulting from data compromised by third party systems. Further, the system may extract and recover data from the third party systems and alter connection channels in order to further limit losses.

US Patent:

20190166152, May 30, 2019

Filed:

Nov 30, 2017

Appl. No.:

15/826893

Inventors:

- Charlotte NC, US
Jason Dean Vaughn - Jacksonville FL, US

International Classification:

H04L 29/06

Abstract:

The invention utilizes a two-component system to detect third party security threats and drive internal system processes based on the detection. The first component of the system is a threat level engine, which collects external and internal system data on a real-time basis to determine changes in conditions that may give rise to a security threat. Based on the external and internal data, the level engine may calculate a threat assessment level to determine the level of the threat. The second component of the system is a third party analytics engine, which may comprise a machine learning component which is configured to detect threat patterns and anomalies, which may in turn be used to trigger events or to drive internal system processes.