公开(公告)号：US11710033B2

公开(公告)日：2023-07-25

申请号：US16006559

申请日：2018-06-12

Applicant: Bank of America Corporation

Inventor： Ronnie J. Morris ,  Dana M. Pusey-Conlin ,  Lorraine C. Edkin ,  Scott A. Sims ,  Joel Filliben ,  Margaret A. Payne ,  Craig Douglas Widmann ,  Eren Kursun

IPC: G06N3/08 ,  G06N3/04 ,  G06F16/26 ,  G06F16/28 ,  G06F16/22

CPC classification number: G06N3/08 ,  G06F16/2291 ,  G06F16/26 ,  G06F16/288 ,  G06N3/04

Abstract: Machine learning models, semantic networks, adaptive systems, artificial neural networks, convolutional neural networks, and other forms of knowledge processing systems are disclosed. An ensemble machine learning system is coupled to a graph module storing a graph structure, wherein a collection of entities and the relationships between those entities forms nodes and connection arcs between the various nodes. A hotfile module and hotfile propagation engine coordinate with the graph module or may be subsumed within the graph module, and implement the various hot file functionality generated by the machine learning systems.

公开(公告)号：US20220286476A1

公开(公告)日：2022-09-08

申请号：US17191377

申请日：2021-03-03

Applicant: BANK OF AMERICA CORPORATION

Inventor： Michael Joseph Carroll ,  Jeffrey Brian Bashore ,  Joel Filliben ,  Andrew DongHo Kim ,  Akhilendra Reddy Kotha ,  Pavan Kumar Reddy Kotlo ,  Ronnie Joe Morris, JR. ,  Dharmender Kumar Satija ,  Michael Shih ,  Scott Anderson Sims ,  Craig D. Widmann

IPC: H04L29/06

Abstract: Embodiments of the invention are directed to a system, method, or computer program product for cross-channel network security with tiered adaptive mitigation operations. In this regard, the invention is structured for dynamic detection of security events associated with network devices and resources, and triggering real-time mitigation operations across a plurality of resource channels. The invention provides a novel method for employing activity data to construct and implement mitigation actions for de-escalating authorization tiers that are adapted to the specific attributes of the activity data, in order to prevent security exposure associated with the activity. Another aspect of the invention is directed to determining whether to continue the tiered adaptive mitigation actions and/or trigger a security proceed signal.

公开(公告)号：US11962617B2

公开(公告)日：2024-04-16

申请号：US17191377

申请日：2021-03-03

Applicant: BANK OF AMERICA CORPORATION

Inventor： Michael Joseph Carroll ,  Jeffrey Brian Bashore ,  Joel Filliben ,  Andrew DongHo Kim ,  Akhilendra Reddy Kotha ,  Pavan Kumar Reddy Kotlo ,  Ronnie Joe Morris, Jr. ,  Dharmender Kumar Satija ,  Michael Shih ,  Scott Anderson Sims ,  Craig D. Widmann

IPC: H04L9/00 ,  H04L9/40

CPC classification number: H04L63/1466 ,  H04L63/105 ,  H04L63/1416 ,  H04L63/1425 ,  H04L63/20

Abstract: Embodiments of the invention are directed to a system, method, or computer program product for cross-channel network security with tiered adaptive mitigation operations. In this regard, the invention is structured for dynamic detection of security events associated with network devices and resources, and triggering real-time mitigation operations across a plurality of resource channels. The invention provides a novel method for employing activity data to construct and implement mitigation actions for de-escalating authorization tiers that are adapted to the specific attributes of the activity data, in order to prevent security exposure associated with the activity. Another aspect of the invention is directed to determining whether to continue the tiered adaptive mitigation actions and/or trigger a security proceed signal.

公开(公告)号：US20230316076A1

公开(公告)日：2023-10-05

申请号：US18207861

申请日：2023-06-09

Applicant: Bank of America Corporation

Inventor： Ronnie J. Morris ,  Dana M. Pusey-Conlin ,  Lorraine C. Edkin ,  Scott A. Sims ,  Joel Filliben ,  Margaret A. Payne ,  Craig Douglas Widmann ,  Eren Kursun

IPC: G06N3/08 ,  G06N3/04 ,  G06F16/26 ,  G06F16/28 ,  G06F16/22

CPC classification number: G06N3/08 ,  G06N3/04 ,  G06F16/26 ,  G06F16/288 ,  G06F16/2291

Abstract: Machine learning models, semantic networks, adaptive systems, artificial neural networks, convolutional neural networks, and other forms of knowledge processing systems are disclosed. An ensemble machine learning system is coupled to a graph module storing a graph structure, wherein a collection of entities and the relationships between those entities forms nodes and connection arcs between the various nodes. A hotfile module and hotfile propagation engine coordinate with the graph module or may be subsumed within the graph module, and implement the various hot file functionality generated by the machine learning systems.