Abstract: Aspects of the disclosure relate to distributed ledgers in OTP verification. A computing platform may receive an event processing request. The computing platform may generate a one time password, and record the one time password in a distributed ledger, and send the one time password to a first device. The computing platform may receive, from a second device, the one time password, which may have been sent from the first device to the second device. Using the distributed ledger, the computing platform may validate the one time password, and may record, in the distributed ledger, validation information indicating that the first one time password was validated. Based on validating the first one time password using the distributed ledger, the computing platform may process a requested event, and may notify the second device that the event was processed.

Abstract: A computer system for optimizing an application for monitoring operation of a network is provided. The application may utilize Artificial Intelligence (AI). The computer system may be configured to detect a network transaction volume level that exceeds a first threshold level. In response to a detection of the network transaction volume level that exceeds a first threshold level, the system may utilize the AI to determine whether to implement one or more over-threshold-level mitigation techniques. When the AI instructs the processor to implement the one or more over-threshold-level mitigation techniques, the system may query the AI for an instruction directing an implementation of the over-threshold-level mitigation techniques.

Abstract: Apparatus and methods for detecting non-linear data dependencies in machine learning are provided. The methods may include receiving a data set comprising a plurality of data features, the data set for processing by a machine learning model operating on a machine learning system. The methods may also include plotting the data set in multi-dimensional space and linearizing the plotted, multi-dimensional space by feeding the plotted data to an algorithm programmed to execute the Delaunay triangulation method. The methods may further include receiving from the algorithm the data set linearized in a faceted space and detecting linear correlations in the linearized data set. The methods may additional include identifying a first data feature that has a correlation coefficient with a second data feature that is greater than an accuracy metric and removing the first data feature from the data set to create a reduced data set.

Abstract: A system for performing optimization of hyper parameters in machine learning typically includes a classical computer apparatus and a quantum optimizer in communication with the classical computer apparatus. The classical computer apparatus is configured for gathering data sets associated with an application, identifying parameters associated with the application, constructing a machine learning model using the data sets and the parameters, determining conditions associated with optimizing the machine learning model, transmitting the machine learning model, the data sets, and the conditions to the quantum optimizer. The quantum optimizer computing a set of optimal hyperparameters for the machine learning model based on the data sets and the conditions and transmitting the set of optimal hyperparameters to the classical computer apparatus.

Abstract: Methods for detecting non-linear data dependencies in machine learning using hybrid quantum computing. Methods include receiving a selection of an accuracy metric. Methods include receiving a data set comprising a plurality of data elements for processing by a machine learning model operating on a machine learning system. Methods include identifying a plurality of data elements within each data set. Methods include identifying one or more features for each data element. Methods include determining a total number of features for the data set. Methods include reducing, by a quantum annealing method, based on the accuracy metric, the total number of features to a reduced number of features. Methods include inputting the reduced number of features into the machine learning model. Methods include outputting a result from the machine learning model.

Abstract: Systems, computer program products, and methods are described herein for augmented hash-based portioning of non-fungible electronic resources for detection of unauthorized duplicates. The present invention is configured to receive an unauthorized duplication detection request for a first NFT from a first user; segment the first digital resource into a first set of resource portions; generate a first set of hash values corresponding to the first set of resource portions; retrieve a second digital resource, wherein the second digital resource is associated with a second NFT; segment the second digital resource into a second set of resource portions; generate a second set of hash values corresponding to the second set of resource portions; determine that the second digital resource is similar to the first digital resource; determine that the second NFT is an unauthorized duplication of the first NFT; and trigger one or more responsive actions.

Abstract: Aspects of the disclosure relate to digital twin simulation. A computing platform may train, using historical property information, a digital twin property evaluation engine, configured to model a physical property based on characteristics of the physical property using a computer simulation. The computing platform may receive, from a client device, an event processing request identifying a first physical property. The computing platform may generate, using the digital twin property evaluation engine, a computer simulation of the first physical property. The computing platform may execute, over a simulated period of time, the computer simulation of the first physical property to output event processing information for the first physical property. The computing platform may send, to the client device, the event processing information and one or more commands directing the client device to display the event processing information, which may cause the client device to display the event processing information.

Abstract: Aspects of the disclosure relate to return logistics. A computing platform may process a first request, resulting in first information indicating a first transfer of resources from a buyer of an item to a seller. The computing platform may record, in a distributed ledger, the first information. The computing platform may receive a second request corresponding to another sale of the item, and may process the second request, which may result in second information indicating a second transfer of resources from another buyer to the seller. The computing platform may record, in the distributed ledger, the second information, and may cause the item to be sent from the buyer to the other buyer. The computing platform may identify, using the distributed ledger, that the item has been received by the other buyer, and may cause a third transfer of resources from the seller to the buyer.

Abstract: Aspects of the disclosure relate to OCR. A computing platform may train, using historical images, a CNN and a RNN to perform OCR/identify characters in context. The computing platform may receive an image of a document, and may input the image into the CNN, which may cause the CNN to output OCR information for the image and a confidence score. Based on identifying that the confidence score exceeds a confidence threshold, the computing platform may store the OCR information to enable subsequent access of a digital version of the document. Based on identifying that the confidence score does not exceed the confidence threshold, the computing platform may: 1) input the OCR information into the first RNN, which may cause the first RNN to output contextual OCR information for the image, and 2) store the contextual OCR information to enable subsequent access of the digital version of the document.

Abstract: Aspects of the disclosure relate to machine learning and quantum computing. A computing platform may receive historical information, which may include feature information and rate of change information. The computing platform may train, a ML model, by inputting the feature information and the rate of change information, which may make the ML model stable against data drift. The computing platform may receive a first query, input the first query into the ML model, to identify a solution to the first query, which may include identifying a first solution, perturbing the first solution a number of times, and ultimately identifying a second solution, more accurate than the first solution. The computing platform may send this second solution to the user device.

Abstract: Aspects of the disclosure relate to user authentication. A computing platform may receive a plurality of facial scans of an individual. The computing platform may train, using the plurality of facial scans, a convolutional neural network (CNN) to identify the individual, based on a first facial scan of the individual, using subclasses of the CNN. The computing platform may receive an authorization request including the first facial scan of the individual. The computing platform may input the first facial scan into the CNN, which may cause the CNN to identify the individual. Based on successful identification of the individual, the computing platform may grant requested access to the individual. The computing platform may update, using the first facial scan, the CNN.

Abstract: Aspects of the disclosure relate to using machine-learning models to determine graduated levels of access to secured data for remote devices. In some embodiments, a computing platform may establish a connection with a mobile device. Subsequently, based on establishing the connection, the platform may identify initial device information, device features, and user information. The platform may input the identified information into an authentication model to compute a baseline authentication score and then may identify an initial level of access to secured resources for the mobile device. Thereafter, the platform may receive from the mobile device, AR/VR device information captured by the mobile device. The platform may input the AR/VR device information into the authentication model to compute an augmented authentication score. Based on the augmented score, the platform may identify an augmented level of access to secured resources for the mobile device.

Abstract: Aspects of the disclosure relate to digital check generation. A computing platform may receive, from a first user device, a digital check generation request, requesting a transfer of funds from an account of a first individual to an account of a second individual. The computing platform may generate, based on the digital check generation request, a first digital check, which may be traceable and configured for cancellation by the first individual prior to deposit. The computing platform may record the first digital check to a distributed ledger. The computing platform may send, to a second user device, a notification of the first digital check. The computing platform may receive, from the second user device, a check processing request requesting one of: a transfer of the first digital check, a deposit of the first digital check, or generation of a second digital check, and may proceed accordingly.

Abstract: Aspects of the disclosure relate to distributed ledgers in OTP verification. A computing platform may receive an event processing request. The computing platform may generate a one time password, and record the one time password in a distributed ledger, and send the one time password to a first device. The computing platform may receive, from a second device, the one time password, which may have been sent from the first device to the second device. Using the distributed ledger, the computing platform may validate the one time password, and may record, in the distributed ledger, validation information indicating that the first one time password was validated. Based on validating the first one time password using the distributed ledger, the computing platform may process a requested event, and may notify the second device that the event was processed.

Abstract: A computing platform may generate a distributed ledger including a plurality of hierarchic element chains, where: 1) data lineage is generated, for each element of each hierarchic element chain at a speed that matches a speed of data entry to the corresponding hierarchic element chain, and 2) at least a first hierarchic element chain is configured to operate at a first speed and at least a second hierarchic element chain is configured to operate at a second speed, slower than the first speed. The computing platform may receive a request to access the data lineage. The computing platform may send one or more commands directing a computing device to display the data lineage, which may cause the computing device to display the data lineage.

Abstract: Aspects of the disclosure relate to digital check processing. A computing platform may receive, from a first recipient, a request to transfer a first portion of funds, corresponding to the first digital check image, to a second recipient account and a second portion of the funds, corresponding to the first digital check image, to a third recipient account. The computing platform may generate second and third digital check images representative of the first and second portions of the funds respectively. Based on successful validation of the second digital check image and the third digital check image, the computing platform may embed, into the second and third digital check images, a digital chip that indicates the successful validation. The computing platform may send, to the second recipient account and the third recipient account, the second and third digital check images respectively.

Abstract: Aspects of the disclosure relate to digital check processing. A computing platform may receive a check image from a user device. The computing platform may configure, based on the check image, a digital check for use in conducting transactions between the user device and point of sale devices, which may include generating a QR code for the check. The computing platform may send, to the user device, the digital check, which may enable the user device to execute a transaction with a first point of sale device. The computing platform may receive, from the first point of sale device, a request to execute the transaction. The computing platform may direct an event processing server to process the transaction, which may cause the event processing server to execute a transfer of funds from an account of the initial payor to an enterprise account of the first point of sale device.

Abstract: A system is provided for machine-learning based identification and filtering of electronic network communication. In particular, the system may continuously monitor and pull electronic communications data from one or more networked computing systems in an enterprise environment. Based on the electronic communications data, the system may use machine learning algorithms to generate a database of associations between one or more users and one or more topics of interest. The system may then output one or more recommendations to one or more users for transmitting communications associated with the one or more topics of interest. In this way, the system may improve the efficiency of communications received and transmitted within a network.

Abstract: Aspects of the disclosure relate to digital check processing. A computing platform may record a first digital check image to a distributed ledger. The computing platform may receive, from first recipient, a request to transfer a first portion of funds to a second recipient account and a second portion of the funds to a third recipient account. The computing platform may modify the distributed ledger to include a second block indicating the transfer, and may grant ledger access permissions to the second and third recipients. The computing platform may direct an event processing server to execute a transfer of the first portion of the funds from an account of an initial payor of the first digital check image to the second recipient account, which may cause the event processing server to execute the transfer of the first portion of the funds.

Abstract: Systems, computer program products, and methods are described herein for frequency filtering in image analysis for identity verification. The present invention is configured to receive, from a user input device, a request from a user to initiate identity verification for access privileges; receive a first image of a face of the user from the user input device in response to the request, wherein the first image is in a geometric domain; transform, using an image transformation algorithm, the first image from the geometric domain into a frequency domain; process, using a machine learning (ML) subsystem, the first image of the user; authenticate the user based on at least processing the first image; and automatically trigger one or more access privilege protocols in response to authenticating the user.