Abstract: Embodiments of the present invention provide a system for generating on-demand single-use biometric authentication credentials. The system is configured for determining initiation of an authentication request to access a resource from a user device of a user, prompting the user to select a type of authentication credential from one or more types of authentication credentials, receiving a selection of the type of the authentication credential, instantaneously generating a single-use unique authentication credential associated with the type of the authentication credential, via one or more machine learning models, and transmitting the single-use unique authentication credential to the user device for use in authentication of the user in gaining accessing to the resource.

Abstract: Arrangements for detecting polymorphic botnets using a pattern matching engine are provided. The platform may train a pattern matching engine to generate image pattern statuses based on a training set of historical image patterns. The platform may automatically generate real-time interaction information based on monitoring interactions between user devices and cloud platforms. The platform may generate a potentially malicious image pattern based on the real-time interaction information. The platform may then input the image pattern into the pattern matching engine to generate an image pattern status for the image pattern. The platform may store the image pattern to a pattern storage repository. Based on identifying the image pattern as malicious, the platform may initiate a security action. The platform may update the pattern matching engine based on the image pattern and its image pattern status to detect future polymorphic botnet attacks.

Abstract: Systems, computer program products, and methods are described herein for determining process compliance using advanced computational models for data analysis and automated decision-making. The present disclosure is configured to generate one or more intermediate control layers, wherein the one or more intermediate control layers comprises one or more artificial intelligence models; generate one or more control objectives, wherein each of the one or more control objectives are associated with one or more governance processes; generate, in response to the one or more control objectives, one or more manifests; receive, in response to the one or more manifests, one or more artifacts, wherein the one or more artifacts comprise data associated with the one or more governance processes; capture data from the one or more artifacts; compare the captured data from the one or more artifacts with the one or more intermediate control layers; and approve the one or more artifacts.

Abstract: Systems, computer program products, and methods are described herein for anomaly detection in hybrid infrastructure deployment environments. The present disclosure is configured to receive and extract code deployment metadata from one or more code repositories and execute a code deployment security protocol on the code deployment metadata. In addition, the present disclosure is configured to transmit the code deployment metadata to a distributed computing environment, wherein the distributed computing environment comprises one or more application platforms. In addition, the present disclosure is configured to receive network data packets from the one or more application platforms via a network gateway. An AI engine determines network anomalies based on the network data packets. The present disclosure also is configured to generate and transmit a notification based on the network anomalies.

Abstract: Embodiments of the invention are directed to systems, methods, and computer program products for identity verification. In some embodiments, the method includes receiving, from a first user device, an identity verification request, the identity verification request comprising information associated with a second user device; based on the identity verification request, generating a link, wherein the link is configured to grant the second user device access to a remote application; receiving, via the remote application, a first image; extracting a first metadata dataset associated with the first image; determining whether the second user is associated with a known entity; based on determining whether the second user is associated with a known entity, launching an identity verification protocol; and based on an output of the identity verification protocol, transmitting a notification to the first user device.

Abstract: A computing platform may train, using historical information migration error information, an information reconciliation engine to predict information migration errors. The computing platform may detect migration of information from a source information system to a target information system. The computing platform may generate, by inputting the information into the information reconciliation engine, a list of predicted migration errors. The computing platform may sample the migrated information to identify a list of real time migration errors. The computing platform may identify corrective actions to address the list of predicted migration errors and the list of real time migration errors. The computing platform may generate, based on the corrective actions, a configuration file.

Abstract: Systems, computer program products, and methods are described herein for determining readiness for managed runtime application program interface (API) applications via artificial intelligence. The present disclosure is configured to scan a set of API applications and their associated custom port hosted within a managed runtime environment using a custom port probe embedded within the managed runtime environment, where the custom port probe is operably coupled to a load balancer, where user traffic within the managed runtime environment is processed by the set of API applications and the custom port; initialize a set of components within the custom port for operation; verify readiness of the set of API application and the custom port probe using an artificial intelligence system; and transmit a notification to the load balancer indicating readiness of the set of API applications.

Abstract: Systems, computer program products, and methods are described herein for selective data routing in a distributed network via data throughput analysis in a distributed ledger network. The present invention is configured to receive a request for a data transmission from an endpoint device of a network, determine, via a routing module, a throughput of data associated with the data transmission, determine a classification of the data transmission, and assign the data transmission to an assigned routing channel. The assigned routing channel may include either a first routing channel or a second routing channel based on the classification, wherein the first routing channel is a light load network, and wherein the second routing channel is a heavy load network comprising a first multicore optical fiber.

Abstract: Arrangements for detecting and resolving anomalies are provided. A computing platform may train an artificial intelligence (AI) engine. The computing platform may configure one or more anomaly detection rules and deploy the one or more anomaly detection rules. The computing platform may receive an encrypted screenshot. The computing platform may decrypt the encrypted screenshot. The computing platform may input the decrypted screenshot into the AI engine. The computing platform may output, based on analyzing the decrypted screenshot using the AI engine, an action to resolve an identified anomaly. The computing platform may execute the action to resolve the identified anomaly.

Abstract: Embodiments of the present invention provide a system for performing authentication of users connecting to entity resources via external systems. The system is configured for determining that a user is requesting to access an entity resource associated with an entity, initiating a verification mechanism for performing verification of the user, authenticating the user based on performing the verification of the user via the verification mechanism, and allowing or denying access to the entity resource based on successful or unsuccessful authentication of the user.

Abstract: Systems, computer program products, and methods are described herein for database configurations using advanced computational models for data analysis and automated processing. The present disclosure is configured to receive a first container record including data associated with a container and store the first container record in a first database. The present disclosure is configured to receive a trigger, wherein the trigger causes a generation of a second container record. The present disclosure is configured to determine a difference between the first container record and the second container record. The difference may affect at least one of an application, a file, or an additional container associated with the container.

Abstract: Systems, computer program products, and methods are described herein for decommissioning applications in an electronic environment.

Abstract: Aspects of the disclosure relate to using multiple machine learning models and a sand-box environment to detect malicious uniform resource locators (URLs) and login pages stored in a QR code. An application on a computing device will augment QR code data stored in a QR code and the computing device sends the QR code data and computing device metadata to a deep learning computing platform. The QR code data may comprise a URL and communication protocol information. The deep learning computing platform will generate, by multiple machine learning models and a sand-box environment, a sand-box score using the URL, a user-based score using the computing device metadata, and a connections score using the communication protocol information. The deep learning platform then determines whether the computing device should reject and delete the QR code data based on whether the scores are below a pre-determined threshold.

Abstract: Embodiments of the invention are directed to systems, methods, and computer program products for provisioning a virtual lab environment for software development. In some embodiments, the method includes defining a set of features in the virtual lab environment; receiving, via a user input on a user interface, an unstructured dataset; generating a structured dataset using a generative artificial intelligence (AI) engine, where the unstructured dataset is an input of the generative AI engine; identifying, based on the structured dataset, a preferred configuration, where the preferred configuration comprises a target set of features; initiating a code delivery process, where the code delivery process includes configuring the set of features in the virtual lab environment to match the target set of features. The method may also include identifying at least one available software agent and displaying the at least one available software agent on the user interface.

Abstract: Systems, computer program products, and methods are described herein for determining readiness for managed runtime application program interface (API) applications via artificial intelligence. The present disclosure is configured to scan a set of API applications and their associated custom port hosted within a managed runtime environment using a custom port probe embedded within the managed runtime environment, where the custom port probe is operably coupled to a load balancer, where user traffic within the managed runtime environment is processed by the set of API applications and the custom port; initialize a set of components within the custom port for operation; verify readiness of the set of API application and the custom port probe using an artificial intelligence system; and transmit a notification to the load balancer indicating readiness of the set of API applications.

Abstract: Embodiments of the present invention provide a system for generating on-demand single-use biometric authentication credentials. The system is configured for determining initiation of an authentication request to access a resource from a user device of a user, prompting the user to select a type of authentication credential from one or more types of authentication credentials, receiving a selection of the type of the authentication credential, instantaneously generating a single-use unique authentication credential associated with the type of the authentication credential, via one or more machine learning models, and transmitting the single-use unique authentication credential to the user device for use in authentication of the user in gaining accessing to the resource.

Abstract: Systems, computer program products, and methods are described herein for reconfiguration authorization protocol and analytics via integrated machine learning. The present disclosure includes receiving a proposed alteration comprising alteration data comprising an application identifier and description data, retrieving at least one configuration item device associated with the application identifier, determining a category of impact based on the alteration data, routing the alteration data to at least one module of a machine learning model, determining dependencies of the proposed alteration based on the application identifier and alteration data, determining a materiality of the proposed alteration, and causing to be displayed, at a first endpoint device, an escalation notice, upon a first condition where the materiality score is above a predetermined threshold.

Abstract: Systems, computer program products, and methods are described herein for enhanced observability within application containers on a container orchestration platform. The present disclosure is configured to: receive an application container within a container orchestration platform, wherein the application container comprises an internal state; embed a container application programming interface (API) within the application container, wherein the container API is linked to an external observability service; transmit a hyper text transfer protocol (HTTP) call from the external observability service to the container API within the application container; observe the internal state of the application container via the container API; and transmit the internal state of the of the application container from the container API to the external observability service.

Abstract: Systems, computer program products, and methods are described herein for automatic mapping of application component dependencies using log analysis. The present disclosure is configured to collect connectivity data from various sources, including log files, service logs, and network packet captures, to automatically identify relationships between applications. The system analyzes the collected data to determine communication protocols, interaction types, and data exchange volumes between the applications. Unique application identifiers are extracted to associate each communication with the correct application. The system persists the determined dependencies and associated metadata in a storage device, and generates visual maps of application relationships for user display. The system is further capable of producing on-demand reports based on user-defined parameters, such as relationship depth and specific communication paths.

Abstract: Arrangements for detecting polymorphic botnets using a pattern matching engine are provided. The platform may train a pattern matching engine to generate image pattern statuses based on a training set of historical image patterns. The platform may automatically generate real-time interaction information based on monitoring interactions between user devices and cloud platforms. The platform may generate a potentially malicious image pattern based on the real-time interaction information. The platform may then input the image pattern into the pattern matching engine to generate an image pattern status for the image pattern. The platform may store the image pattern to a pattern storage repository. Based on identifying the image pattern as malicious, the platform may initiate a security action. The platform may update the pattern matching engine based on the image pattern and its image pattern status to detect future polymorphic botnet attacks.