公开(公告)号：US12164867B1

公开(公告)日：2024-12-10

申请号：US18356435

申请日：2023-07-21

Applicant: Capital One Services, LLC

Inventor： Jeremy Goodsitt ,  Galen Rafferty ,  Samuel Sharpe ,  Brian Barr ,  Taylor Turner ,  Kenny Bean

IPC: G06F40/194 ,  G06F40/284

Abstract: In some implementations, a device may obtain a first document set associated with a first code repository. The device may generate a first embedding set of one or more embeddings for respective documents included in the first document set. The device may obtain a second embedding set of one or more embeddings for respective documents included in a second document set associated with a second code repository. The device may compare the first embedding set to the second embedding set. The device may generate a code repository similarity score that indicates a similarity between the first code repository and the second code repository. The device may perform, based on the code repository similarity score satisfying a threshold, an action associated with the first code repository and/or the second code repository.

公开(公告)号：US20240412219A1

公开(公告)日：2024-12-12

申请号：US18330606

申请日：2023-06-07

Applicant: Capital One Services, LLC

Inventor： Taylor Turner ,  Galen Rafferty ,  Samuel Sharpe ,  Brian Barr ,  Jeremy Goodsitt ,  Michael Davis ,  Justin Au-Yeung ,  Owen Reinert

IPC: G06Q20/40

Abstract: Disclosed embodiments may include a system for fraud detection. The system may identify, using a web browser extension, that a user has navigated to a webpage on a user device. The system may receive, via the webpage, data associated with a transaction. Responsive to receiving the data, the system may retrieve search history data corresponding to a searching session associated with the data, and may identify a searching session path corresponding to the transaction. The system may determine, using a machine learning model (MLM) and based on the search history data and the searching session path, a likelihood of fraud associated with the data. The system may determine whether the likelihood exceeds a predetermined threshold. Responsive to determining the likelihood exceeds the predetermined threshold, the system may conduct one or more fraud prevention actions.

公开(公告)号：US20240370839A1

公开(公告)日：2024-11-07

申请号：US18311824

申请日：2023-05-03

Applicant: Capital One Services, LLC

Inventor： Samuel Sharpe ,  Brian Barr ,  Michael Davis ,  Taylor Turner ,  Justin Au-Yeung ,  Tyler Farnan ,  Galen Rafferty

IPC: G06Q20/10

Abstract: Disclosed embodiments may include a system for executing programmable macros based on external device interactions. The system may include one or more processors, and a memory in communication with the one or more processors and storing instructions that, when executed by the one or more processors, are configured to cause the system to execute programmable macros based on external device interactions. The system may receive a device identification of an external device. The system may receive a rule associated with the external device, wherein the rule comprises a triggering event and transfer instructions. The system may receive, from the external device, device data. Responsive to determining, from the device data, that the triggering event has occurred, the system may execute the transfer instructions.

公开(公告)号：US12164677B2

公开(公告)日：2024-12-10

申请号：US18063394

申请日：2022-12-08

Applicant: Capital One Services, LLC

Inventor： Jeremy Goodsitt ,  Michael Davis ,  Taylor Turner ,  Kenny Bean ,  Tyler Farnan

IPC: G06F21/64 ,  G06N3/098

Abstract: Methods and systems are described for novel uses and/or improvements to federated learning. As one example, methods and systems are described for improving the applicability of federated learning across various applications and increasing the efficiency of training a global model through federated learning. As another example, methods and systems are described for ensuring comprehensive training data is available to models assigned by the federated learning server. Additionally, methods and systems are described for improving the rate of training a global model through federated learning.

公开(公告)号：US20240283822A1

公开(公告)日：2024-08-22

申请号：US18170492

申请日：2023-02-16

Applicant: Capital One Services, LLC

Inventor： Galen RAFFERTY ,  Samuel Sharpe ,  Brian Barr ,  Jeremy Goodsitt ,  Michael Davis ,  Taylor Turner ,  Justin Au-Yeung ,  Owen Reinert

IPC: H04L9/40 ,  H04L41/16

CPC classification number: H04L63/1491 ,  H04L41/16 ,  H04L63/1416

Abstract: In some aspects, a computing system may iterate between adding spurious data to the dataset and training a model on the dataset. If the model's performance has not dropped by more than a threshold amount, then additional spurious data may be added to the dataset until the desired amount of performance decrease has been achieved. the computing system may determine the amount of impact each feature has on a model's output. The computing system may generate a spurious data sample by modifying values of features that are more impactful than other features. The computing system may repeatedly modify the spurious data that is stored in a dataset. If a cybersecurity incident occurs (e.g., the dataset is stolen or leaked), the system may identify when the cybersecurity incident took place based on the spurious data that is stored in the dataset.