Abstract: A computing platform to generate and manage businesses for users. An artificial intelligence/machine learning (AI/ML) model is continually trained to identify user interests and hobbies that may be transformed into business ventures. The computing platform aggregates electronic data about activities or transactions performed via applications computing systems providing products or services to users. The computing platform facilitates generation of a new business based on prioritized feature sets. The AIMI generates and creates management tools such as business plans that include financial plans, marketing plans, human resource plans, competitor environment analysis, and other management tools for successful operation of the new business.

Abstract: A system is provided for secure cross partition access and computing device recovery. In particular, the system may comprise a computing device that includes a non-transitory memory or storage device comprising one or more partitions. A user may attempt to log into the device and get locked out of the primary partition of the device after a threshold number of unsuccessful login attempts. The additional partitions of the computing device may store a portion of the authentication credential needed to access the primary partition and prompt the user using an item from the user data stored in a user-specific database. Upon detecting that the user has successfully accessed a threshold number of partitions and/or successfully provided responses to the prompts from a threshold number of partitions, the system may unlock and grant access to the locked partitions.

Abstract: A computing platform may generate a schema to prompt for user access information, wherein the user access information includes: 1) a set of authorized users and 2) one or more portions of an information source to which the set of authorized users have access. The computing platform may send, to a first user device, the schema. The computing platform may receive, from the first user device, the user access information. The computing platform may translate the user access information to structured user information, which may include translating the user access information from a first format into a second format. The computing platform may send, to a second user device corresponding to one of the set of authorized users, the structured user information.

Abstract: A proof of game validation system provides an efficient process to validate newly added blocks to a blockchain based on a result of a competitive entertainment activity. The proof of game validation system identifies a type of competitive online entertainment activity and determines a number of devices based on the complexity of the competitive online activity. Pairs of user devices participating in the competitive online activity and validator computing devices vying to validate a new block of the blockchain are randomly generated from a pool of user devices and validator computing devices. At a completion of the competitive online activity, the winning pair is rewarded. The proof of game validation system triggers transfer of a reward to a digital wallet of the winning user device and triggers a validation process for the blockchain to be performed by the winning validator computing device.

Abstract: Systems, computer program products, and methods are described herein for implementing AI to generate a time-sensitive notifications related to configuration of graphical user interfaces. The present invention is configured to identify a primary user account; collect a primary user account dataset; generate a time sensitive notification AI engine associated with the primary user account; access, by the time sensitive notification AI engine, a user account database; identify at least one comparable user account and an associated at least one comparable user account dataset; compare, by the time sensitive notification AI engine, the primary user account dataset and the at least one comparable user account dataset; generate a time sensitive notification for the primary user account; and transmit a time sensitive notification interface component to a user device associated with the primary user account.

Abstract: Systems, methods, and computer program products are provided herein for image authenticated data transfers between electronic devices in a distributed network. An example method includes receiving a request for data transfer from a first user device associated with a first user that defines one or more data transfer parameters and determining a second user associated with the data transfer request based upon the one or more data transfer parameters. The method also includes determining a verifiable image object associated with the second user that includes at least a digital representation of the second user. The method further includes authenticating the data transfer between the first user device and a second user device associated with the second user in response to an authentication operation by the first user based upon the verifiable image object.

Abstract: A network system of pattern analysis includes a centralized AI-based pattern analysis engine and each computing device comprises a local AI-based pattern analysis engine. The pattern analysis engine(s) each analyze computing operations on a local machine basis or a on a network basis depending on where installed. The AI-based pattern analysis engines identify common activity patterns for each machine and exclude the common activity patterns from further analysis of the computing operations, leading to more efficient identification of activity patterns indicative of nefarious activity. Once detected, the AI-based pattern analysis engines trigger an incident response to counter the nefarious activities. The AI-based pattern analysis engines include AI models that are continually or periodically trained to update the baseline common activity patterns.

Abstract: A network system of pattern analysis includes a centralized AI-based pattern analysis engine and each computing device comprises a local AI-based pattern analysis engine. The pattern analysis engine(s) each analyze computing operations on a local machine basis or a on a network basis depending on where installed. The AI-based pattern analysis engines identify common activity patterns for each machine and exclude the common activity patterns from further analysis of the computing operations, leading to more efficient identification of activity patterns indicative of nefarious activity. Once detected, the AI-based pattern analysis engines trigger an incident response to counter the nefarious activities. The AI-based pattern analysis engines include AI models that are continually or periodically trained to update the baseline common activity patterns.

Abstract: Systems, computer program products, and methods for detecting and preventing malfeasant activity based on patterns in malfeasant activity are provided. The method includes receiving a plurality of communication data packets associated with one or more online forums. Each communication data packet includes communication(s) within a conversation on the online forum(s). The method also includes determining a first malfeasant communication data packet of the plurality of communication data packets. The malfeasant communication data packet is associated with a conversation in which malfeasant activity is being discussed. The method further includes determining first malfeasant activity characteristic(s) from the first malfeasant communication data packet indicative of malfeasant activity. The method also includes detecting a potential malfeasant activity based on at least one of the first malfeasant activity characteristic(s).

Abstract: Methods and apparatus for parallel intent processing at a network of chatbots may be provided. A query may be received at a user interface. The query may be transmitted to multiple chatbots at the same time. Each chatbot may identify an intent for the query. Each chatbot may also identify a percentage of accuracy that the chatbot considers that the intent corresponds to the query. The chatbots may present the intents to the user interface. The user interface may rank the intents. The user interface may display the ranked intents to the user. The user interface may receive an intent selection from the user. The user interface may direct the user to the chatbot that identified the selected intent.

Abstract: Apparatus and methods for automating replacement and disablement of one-time password (“OTP”) generators are provided. The apparatus and methods may include an authentication engine on a server and an OTP generator that may generate a standard OTP or an enhanced OTP that includes additional information beyond the standard OTP. The authentication engine may analyze the additional information when an enhanced OTP is received, and in response to that additional information, execute an operation. The operation may include initiating the sending of a new OTP generator to a user when the OTP generator's battery is failing or the OTP generator has been damaged or disabling an OTP generator when the OTP generator has been tampered with.

Abstract: Due to the proliferation of protected services that are secured by password wall, a user frequently has to remember multiple complex passwords. There is a need to reduce the number of passwords and maintain adequate security of the protected services. Systems described herein may autogenerate dynamic passwords for those apps that require a password. Protected services may allow user access based on the autogenerated dynamic password. The system may include an API for interacting with multiple apps that each provide protected services. The API may provide dynamic passwords that authenticate a user to access any of the protected services provided by any of the multiple apps.

Abstract: Methods for reducing storage demands at a centralized database and for reducing probability of a security breach such as an interception attack and a man-in-the-middle attack. Methods may include obtaining a document at the edge computing device. Methods may further include storing the document at the edge computing device. Methods may include executing, using a processor, on the edge computing device, a hashing algorithm on the document. Methods may include outputting, using the processor, a hash-value that is an outcome of the hashing algorithm, where the hash-value corresponds to the document. Methods may include transmitting, using the processor, the hash-value to the centralized database over a low bandwidth communication line while maintaining a storage of the hash-value at the edge computing device. Methods may include storing the hash-value at the centralized database. The hash-value may provide a condensed representation of the document.

Abstract: Arrangements for providing software vulnerability analysis and monitoring are provided. In some aspects, software bill of materials (SBOM) data may be received and software attributes may be extracted from the SBOM data. Author data may be received and analyzed using natural language processing and/or machine learning to identify author attributes. Current event or vulnerability data may be received. In some examples, one or more machine learning models may be executed to determine a confidence score associated with the software being analyzed. For instance, software attributes, author attributes, and current event data may be used as inputs in the machine learning model and a confidence score may be output. Based on the confidence score, one or more alerts may be generated and transmitted to one or more enterprise organization computing devices.

Abstract: A system for horizontal scaling of retraining machine learning models across operational domains is provided. The system may reduce computational overhead associated model retraining. The system may include an artificial intelligence (“AI”) engine that determines target machine learning models that need to be retrained in response to changed training data. The AI engine may assign daemons to the target models. The daemons may gather retraining requirements such as source code and training data. The daemons may schedule the target models for retraining on a CPU or a GPU based model training system.

Abstract: A system includes a user device and a computing system. The user device accesses a plurality of images captured by a camera and identifies, from the plurality of images, a particular image that depicts a portion of a user interaction object. The user device transmits the particular image across a wireless communications network. The computing system accesses the particular image depicting the portion of the user interaction object and determines a data item from the particular image. The computing system compares the data item to one or more accounts of the user and sends instructions to the user device to display an alert message on the electronic display based on the comparison of the data item to the one or more accounts.

Abstract: Aspects of the disclosure relate to a method of generating a personalized payment card. In some arrangements, the generated payment card may include on board circuitry and architecture to prevent unauthorized use of the payment card. In some instances, the generated payment card may be a temporary payment card with a fixed transaction limit amount that may or may not be reloadable. The designed personalized payment card may be 3D printed and initialized by a card generating and alerting computing platform.

Abstract: Various aspects of the disclosure relate to bi-directional hybrid-feedback driven self-healing and self-scaling language transpiler system may include bi-directional hopping to support multi language transpilation, automatic conversion of a mapping into a transformation specification, a hybrid feedback mechanism to update the transformation mappings, automatic scaling and/or creation of enterprise wide mapping and token (e.g., grammar) vocabulary, and/or a self-healing and/or corrective translation capability to perform automatic correction of any partial transpilations over time from a learned mapping.

Abstract: Systems, computer program products, and methods are described herein for secure user identification using digital image processing. The present invention is configured to receive, via a first user input device, an input selection of a first image from a first user, wherein the first image is associated with a second user; extract features of the first image; determine a secure image matching the first image based on at least the features of the first image; extract, from the secure image, a unique device identifier associated with the second user embedded thereon; and transmit control signals configured to cause the first user input device to display the unique device identifier.

Abstract: A vault encryption abstraction framework computing system provides interface functionality to facilitate integration of client applications with vaulting solutions. The vault encryption abstraction framework manages custom authentication and authorization using the vaulting solution application for one or more client applications such as by periodically rotating or renewing any authentication tokens. The vault encryption abstraction framework includes a scheduler to manage timing requirements and to configure the client application to the schedule by setting the renewed token value to an API endpoint (e.g., a function return) and/or a configuration file for access by one or more client applications. This event triggers the client application to update to the latest token value. The vault encryption abstraction framework then triggers the vaulting solution to create and return the new key. The new key is then returned to the client application.