Capital One Services, LLC

Jeremy Edward Goodsitt

Austin Grant Walters

Vincent Pham

Anh Truong

Fardin Abdi Taghi Abad

Reza Farivar

Mark Watson

Galen Rafferty

Kenneth Taylor

Kate Key

Samuel Sharpe

Grant Eden

Mark Louis Watson

Ernest Kwak

Brian Chandler Barr

Alvin Hua

Christopher Wallace

Taylor Turner

Kenny Bean

Michael Davis

Micah Price

Melissa A Crawford

Ahn Truong

Noriaki Tatsumi

Tyler Farnan

Justin Au-yeung

Owen Reinert

Paul Hurlocker

Michael Kubiske

Robert P Seaton

Fardin Abdi Abad

Michael Walters

Daniele Rosa

Fardin Abdi Tagh Abad

Fardi Abdi Taghi Abad

Anh Troung

Fardin Abdi Taghi

Techniques for providing a secure mesh network based on a cryptocurrency blockchain are provided. An electronic device can receive data from a mesh network to establish the device as a node on the mesh network. The established node can generate a cryptocurrency wallet that can be loaded with an amount of cryptocurrency. The established node can receive a payment for facilitating transfers on the mesh network including routing transactional or communication data. Public and/or private keys associated with the cryptocurrency wallets can be used to encrypt communications, thereby providing a secure mesh network. Further, the blockchain, which can be managed by one or more authorized nodes of the mesh network, can provide a payment system within the mesh network. The distributed nature of the mesh network allows it to operate securely without a central authority. In turn, the mesh network is more adaptable and flexible.

System and method for creating a secure mesh network utilizing the blockchain

Methods and systems for scalable dataset content embedding for improved searchability. For example, the system may retrieve a first dataset from a first data source. The system may generate a first data profile of the first dataset. The system may generate a latent index of the first data profile based on processing the first data profile using a first embedding algorithm. The system may receive, via a user interface, a first request for a first text string. The system may generate an embedded request corresponding to the first request based on processing the first text string using the first embedding algorithm. The system may process the embedded request using the latent index. The system may generate for display, in the user interface, a result based on processing the embedded request using the latent index.

Systems and methods for scalable dataset content embedding for improved database searchability

Exemplary embodiments may provide an approach to converting multidimensional color data for an image encoded in a first color space into an intermediate form that is a single dimensional value. The exemplary embodiments may then decode the intermediate form value to produce an encoding of the color data that is encoded in a second color space that differs from the first color space. In this manner, the data for the image may be efficiently converted from an encoding in the first color space into an encoding in the second color space.

Color conversion between color spaces using reduced dimension embeddings

Disclosed herein are system, method, and computer program product embodiments for process corruption prevention. An embodiment operates by determining security vulnerabilities for an entity and correlation values for the security vulnerabilities by applying completed processed records of the entity to a machine learning model. Each of the correlation values quantifies a relationship strength between a security vulnerability and fraudulent activity. The embodiment further operates by generating a security vulnerability score for the entity using the correlation values and identifying one or more patches for at least one of the security vulnerabilities. The one or more patches may be ranked and the ranking may be revised using a feedback mechanism after the one or more patches are implemented by the entity.

Patching security vulnerabilities using machine learning

An apparatus includes a display, a memory, a light sensor array and a light source array. The light source array emits light to display an image on the display. A controller is configured to receive a sensor output from each light sensor in the light sensor array. An ambient-light illuminance difference between a first illuminance of a first ambient light externally directed onto a first region of the displayed image of the display and a second illuminance of a second ambient light externally directed respectively onto a second region of the displayed image of the display is computed. Light source controls of light sources of the light source array are varied to change a luminous emittance of the light source array within the at least one second region of the displayed image so as to reduce a luminance difference between the first region and the second region of the displayed image.

Systems and methods for correcting ambient-light illuminance differences of ambient light directed onto regions of a display

Techniques for providing a localized blockchain that uses a mesh network to facilitate transactions for a localized event are provided. An electronic device can receive data from a localized mesh network to establish the device as a node on the localized mesh network. The established node can generate a cryptocurrency wallet that can be loaded with an initial amount of localized cryptocurrency tokens from a total amount of localized cryptocurrency tokens. The total amount of localized cryptocurrency tokens can be previously mined by a central authority of the localized mesh network. The established node can conduct transactions within the localized mesh network utilizing the localized cryptocurrency tokens. The established node can receive a portion of a cryptocurrency token for transmitting transactional data to a next nearest node on the localized mesh network to help facilitate a transaction involving other nodes on the network.

Localized blockchain utilizing mesh networks for localized events

Disclosed embodiments may include systems and methods for utilizing gesture-based transaction cards. Examples include: first, using a mobile device to preauthorize transaction cards to enter an unlocked state before making a purchase by making a gesture with the transaction card toward the mobile device. Second, using a first transaction card to change an authorization condition of a second transaction card associated with the same account by making a gesture from the first transaction card to the second transaction card. Third, using a first transaction card to distribute a predebited virtual card to the user device of a second user by making a gesture from the first transaction card to the user device of the second user. Additionally, the primary user may be able to upload new authorization conditions to the transaction card and control the system through a related mobile application on a connected mobile device.

Systems and methods for authorizing a transfer

Systems and methods for novel uses and/or improvements to data labeling applications, particularly data labeling applications involving sensitive data. As one example, systems and methods are described herein for preventing sensitive data leakage, using weak learner libraries, during label propagation.

Systems and methods for preventing sensitive data leakage during label propagation

A system for returning synthetic database query results. The system may include a memory unit for storing instructions, and a processor configured to execute the instructions to perform operations comprising: receiving a query input by a user at a user interface; determining, based on natural language processing, a type of the query input; determining, based on the received query input and a database language interpreter, an output data format; returning, based on a generation model and the output data format, a result of the query input; providing, to a plurality of training models and based on the determined query type, the query input and the result; and training the training models, based on the query input and the result.

Systems and methods for synthetic database query generation

A device may receive a preauthorization associated with missed transaction prevention for a transaction account of a user, wherein the missed transaction prevention involves preventing a missed transaction associated with merchant accounts of the user. The device may monitor a transaction log of the transaction account and identify a transaction pattern associated with a merchant account based on a plurality of historical transactions identified in the transaction log related to the merchant account. The device may determine that a historical transaction of the plurality of historical transactions is not designated for automatic execution and that an execution of an upcoming transaction corresponding to the plurality of historical transactions is not scheduled. The device may cause an account transaction associated with the upcoming transaction to be automatically executed before a transaction period expiration, associated with the merchant account, passes.

Automatic transaction execution based on transaction log analysis

In some aspects, a computing system obtain a first dataset including a set of original data samples. The computing system may generate a key that indicates a location within the first dataset where spurious data should be stored. The computing system may determine a modified value associated with a first data sample of the set of original data samples, where the modified value causes a machine learning model to generate output that does not match a label associated with the first data sample. Based on the first data sample, the computer system may generate a spurious data sample comprising the modified value. Based on the key, the computer system may add the spurious data sample to the first dataset. In some aspects, based on a request for the first dataset, the computing system may remove the spurious data sample from the first dataset.

Generation of effective spurious data for model degradation

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.

Layered cybersecurity using spurious data samples

A computer-implemented method may include: receiving financial information regarding a user; categorizing transaction information of the user based on the financial information; displaying the categorized transaction information of the user; receiving information regarding at least one financial preference and at least one transaction preference of the user; training a machine learning engine based on the at least one financial preference and at least one transaction preference of the user to determine one or more activities available to the user; calculating, for each of the one or more activities available to the user, an estimated influence on the at least one financial preference; displaying the estimated influence on the at least one financial preference based on a user selected one of the one or more activities available to the user; filtering the one or more activities available to the user with a positive estimated influence to the at least one financial preference; and presenting a recommendation of action relating to the one of the one or more activities available to the user, wherein the recommendation of action relating to the one of the one or more activities available to the user is presented by at least one of voice notification, application notification, tactile notification, or graphic notification.

Systems and methods for debt management with spending recommendation

In the disclosed transaction processing system, members of an authorized network of consumers and merchants manage account information using blockchain ledgers. Because both consumers and merchants maintain copies of the blockchain, for any consumer/merchant transaction, both entities can quickly validate the transaction because both are aware, via their blockchain entries, of the current status of the account sourcing the transaction, allowing fast and accurate transaction validation without the need to incur the processing charges inherent in traditional fiat currency credit transactions.

System and method for authorizing transactions in an authorized member network

Systems and methods for censoring text-based data are provided. In some embodiments a censoring system may include at least one processor and at least one non-transitory memory storing application programming interface instructions. The censoring system may be configured to perform operations comprising storing a target pattern type and a computer-based model for identifying a target data pattern corresponding to a target pattern type within text based data. The censoring system may also be configured to receive text-based data by a server, and to retrieve the stored target pattern type to be censored in the text-based data. The censoring system may be configured to identify within the received text-based data, a target data pattern corresponding to the retrieved target pattern type. The censoring system may be configured to censor target characters within the identified target data pattern, and transmit the censored text-based data to a receiving party.

Growing community of inventors

Champaign, IL, United States of America

Jeremy Edward Goodsitt